Publications

PATENTS

1. T.D. Pham, System, Computer-Readable Storage Medium and Method of Deep Learning of Texture in Short Time Series, U.S. Patent number: 10950352, Date of patent: March 16, 2021.

BOOKS

1. T.D. Pham, Fuzzy Recurrence Plots and Networks with Applications in Biomedicine.  Springer Nature, Switzerland, 2020. 

2. Z. Chi, H. Yan and T. Pham, Fuzzy Algorithms: With Applications to Image Processing and Pattern Recognition. World Scientific, Singapore, 1996. 

3. S. Valliappan and T.D. Pham, Fuzzy Logic Applied to Numerical Modelling of Engineering Problems. Elsevier Science, North-Holland, 1995. 

PAPERS IN REFEREED JOURNALS

1. T.D. Pham, T. Tsunoyama, Exploring extravasation in cancer patients, Cancers, 16 (2024) 2308. DOI:10.3390/cancers16132308

2. T.D. Pham, S.B. Holmes, L. Zou, M. Patel, P. Coulthard, Diagnosis of pathological speech with streamlined features for long short-term memory learning, Computers in Biology and Medicine, 170 (2024) 107976.  DOI: 10.1016/j.compbiomed.2024.107976.

3. T.D. Pham, S.B. Holmes, M. Patel, P. Coulthard, Features and networks of the mandible on computed tomography, Royal Society Open Science, 11 (2024) 231166. DOI: 10.1098/rsos.231166.

4. T.D. Pham, S.B. Holmes, P. Coulthard, A review of artificial intelligence for the diagnosis of fractures in facial trauma imaging, Frontiers in Artificial Intelligence, section: Medicine and Public Health, 6 (2024) 1278529. DOI: 10.3389/frai.2023.1278529

5. T.D. Pham, X.F. Sun, Wavelet scattering networks in deep learning for discovering protein markers in a cohort of Swedish rectal cancer patients, Cancer Medicine, 12 (2023) 21502-21518. DOI: 10.1002/CAM4.6672.

6. D.T.P. Le, T.D. Pham, Unveiling the role of artificial intelligence for wound assessment and wound healing prediction, Exploration of Medicine, 4 (2023) 586–611. https://doi.org/10.37349/emed.2023.00163.

7. T.D. Pham, Deep time-recurrence features, EPL (Europhysics Letters), 142 (2023) 51001.

8. T.D. Pham, Prediction of five-year survival rate for rectal cancer using Markov models of convolutional features of RhoB expression on tissue microarray, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 20 (2023) 3195-3204.

9. V. Ravi, T.D. Pham, M. Alazab, Deep learning-based network intrusion detection system for Internet of Medical Things, IEEE Internet of Things Magazine, 6 (2023) 50-54.

10. T.D. Pham, Classification of motor-imagery tasks using a large EEG dataset by fusing classifiers learning on wavelet-scattering features, IEEE Transactions on Neural Systems & Rehabilitation Engineering, 31 (2023) 1097-1107.

11. T.D. Pham, V. Ravi, N. Liu, B. Luo, X.F. Sun, Tensor decomposition of largest convolutional eigenvalues reveals pathological predictive power of RhoB in rectal cancer biopsy, The American Journal of Pathology,  193 (2023) 579-590.

12. T.D. Pham, V. Ravi, C.W. Fan, B. Luo, X.F. Sun, Classification of IHC images of NATs with deep learning and fuzzy recurrence plots for predicting survival rates of rectal-cancer patients, IEEE Journal of Translational Engineering in Health and Medicine, 11 (2023) 87-95. 

13. R. Chaganti, V. Ravi, T.D. Pham, A multi-view feature fusion approach for effective malware classification using deep learning, Computers & Security,  72 (2023) 103402. 

14. T.D. Pham, V. Ravi, B. Luo, C. Fan, X.F. Sun, Artificial intelligence fusion for predicting survival of rectal cancer patients using immunohistochemical expression of Ras homolog family member B in biopsy, Special Issue "Artificial Intelligence for Precision Oncology", Exploration of Targeted Anti-Tumor Therapy, 4 (2023) 889-904.

15. Q. Yu, H. Yu, Y. Wang, T.D. Pham, SUM-GAN-GEA: Video summarization using GAN with Gaussian distribution and external attention, Electronics, 11 (2022) 3523. 

16. T.D. Pham, Identifying critical transitions in major depression with fuzzy recurrence entropy, All Life, 15 (2022) 1086-1100.

17.  R. Chaganti, V. Ravi, T.D. Pham, Image-based malware representation approach with EfficientNet convolutional neural networks for effective malware classification, Journal of Information Security and Applications, 69 (2022) 103306.

18.  V. Ravi, T.D. Pham, Unsupervised deep learning-based feature fusion approach for detection and analysis of COVID-19 using X-ray and CT images, The Open Bioinformatics Journal, vol. 15, publisher item identifier: EA-TOBIOIJ-2022-7, 2022.

19.  V. Ravi, T.D. Pham, M. Alazab, Attention-based multidimensional deep learning approach for cross-architecture IoMT malware detection and classification in healthcare cyber-physical systems, IEEE Transactions on Computational Social Systems, 10 (2023) 1597-1606.

20. R. Chaganti, V. Ravi, T.D. Pham, Deep learning based cross architecture Internet of Things malware detection and classification, Computers & Security, 120 (2022) 102779.

21. I. Andronache, D. Peptenatu, H. Ahammer, R. Taylor, I. Liritzis, M. Radulovic, B. Ciobanu, M. Burcea, M. Perc, T.D. Pham, et al.,   Kolmogorov compression complexity may differentiate different schools of Orthodox iconography, Scientific Reports, 12 (2022) 10743.

22. P. Yadav, N. Menon, V. Ravi, S. Vishvanathan, T.D. Pham, A two-stage deep learning framework for image-based Android malware detection and variant classification, Computational Intelligence, 38 (2022) 1748-1771.

23. T.D. Pham, Kriging-weighted Laplacian kernels for grayscale image sharpening, IEEE Access, 10 (2022) 57094-57106.

24. T.D. Pham, Quantification analysis of fuzzy recurrence plots, EPL (Europhysics Letters), 137 (2022) 62002.

25. T.D. Pham, Classification of Caenorhabditis elegans locomotion behaviors with eigenfeature-enhanced long short-term memory networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 20 (2023) 206-216. 

26. V. Ravi, H. Narasimhan, T.D. Pham, A cost-sensitive deep-learning based meta-classifier for pediatric pneumonia classification using chest X-rays, Expert Systems, 39 (2022) e12966. 

27. P. Yadav, N. Menon, V. Ravi, S. Vishvanathan, T.D. Pham, EfficientNet convolutional neural networks-based Android malware detection, Computers & Security, 115 (2022) 102622.

28. V. Ravi, V. Acharya, T.D. Pham, Attention deep learning based large-scale learning classifier for Cassava leaf disease classification, Expert Systems, e12862, 2021. https://doi.org/10.1111/exsy.12862

29. T.D. Pham, Recurrence eigenvalues of movements from brain signals, Brain Informatics, 8 (2021) article number 22.

30. V. Acharya, V. Ravi, T.D. Pham, C. Chakraborty, Peripheral blood smear analysis using automated computer-aided diagnosis system to identify acute myeloid leukemia, IEEE Transactions on Engineering Management, 70 (2023) 2760-2773.

31. T.D. Pham, Fuzzy recurrence exponents of subcellular-nanostructure dynamics in time-lapse confocal imaging, IEEE Transactions on NanoBioscience, 20 (2021) 497-506. 

32. T.D. Pham, From raw pixels to recurrence image for deep learning of benign and malignant mediastinal lymph nodes on computed tomography, IEEE Access, 9 (2021) 96267-96278.

33. A. Arunachalam, V. Ravi, V. Acharya, T.D. Pham, Towards data-model-agnostic autonomous machine-generated data labeling and annotation platform: COVID-19 auto-annotation use case, IEEE Transactions on Engineering Management, 70 (2023) 2695-2706.

34. T.D. Pham, Convolutional fuzzy recurrence eigenvalues, EPL (Europhysics Letters), 135 (2021) 20002. 

35. T.D. Pham, Time-frequency time-space long short-term memory networks for image classification of histopathological tissue, Scientific Reports, 11 (2021) 13703. DOI: 10.1038/s41598-021-93160-5

36. V. Ravi, H. Narasimhan, C. Chakraborty, T.D. Pham, Deep learning based meta-classifier approach for COVID-19 classification using CT scan and chest X-ray images, Multimedia Systems, published online 06 July 2021, https://doi.org/10.1007/s00530-021-00826-1.

37. T.D. Pham, Time-frequency time-space LSTM for robust classification of physiological signals, Scientific Reports, 11 (2021) 6936.

38. M.D. Cirillo, R. Mirdell, F. Sjoberg, T.D. Pham, Improving burn depth assessment for pediatric scalds by AI based on semantic segmentation of polarized light photography images, Burns, 47 (2021) 1586-1593.

39. T.D. Pham, Classification of COVID-19 chest X-rays with deep learning: new models or fine tuning?, Health Information Science and Systems, 9 (2021) 2. https://doi.org/10.1007/s13755-020-00135-3

40. S. Zhang, H. Yu, T. Wang, J. Dong, T.D. Pham, Linearly augmented real-time 4D expressional face capture, Information Sciences, 545 (2021) 331-343 .

41. T.D. Pham, A comprehensive study on classification of COVID-19 on computed tomography with pretrained convolutional neural networks, Scientific Reports, 10 (2020) 16942. Mentioned in news by Becker’s Hospital Review as 6 recent key studies exploring AI in healthcare: “6 recent studies exploring AI in healthcare”, Katie Adams, October 9th, 2020: https://www.beckershospitalreview.com/artificial-intelligence/6-recent-studies-exploring-ai-in-healthcare.html

42. X. Liu, Y. Xia, H. Yu, J. Dong, M. Jian, T.D. Pham, Region based parallel hierarchy convolutional neural network for automatic facial nerve paralysis evaluation, IEEE Trans Neural Systems & Rehabilitation Engineering, 28 (2020) 2325-2332 

43. T.D. Pham, C. Fan, H. Zhang, X.-F. Sun, Artificial intelligence-based 5-year-survival prediction and prognosis of DNp73 expression in rectal cancer patients, Clinical and Translational Medicine, 10 (2020) e159. DOI: 10.1002/ctm2.159.

44. T.D. Pham, Fuzzy recurrence entropy, EPL (Europhysics Letters), 130 (2020) 40004.

45. T.D. Pham, Fuzzy cross and fuzzy joint recurrence plots, Physica A: Statistical Mechanics and its Applications, 540 (2020) 123026.

46. T.D. Pham, C. Fan, D. Pfeifer, H. Zhang, X.-F. Sun, Image-based network analysis of DNp73 expression by immunohistochemistry in rectal cancer patients, Frontiers in Physiology, section: Computational Physiology and Medicine, 10 (2019) 1551. DOI: 10.3389/fphys.2019.01551.

47. T.D. Pham, K. Wardell, A. Eklund, G. Salerud, Classification of short time series in early Parkinson's disease with deep learning of fuzzy recurrence plots, IEEE/CAA Journal of Automatica Sinica, 6 (2019) 1306-1317. News release 25/12/19 at AAAS and EurekAlert!: https://www.eurekalert.org/pub_releases/2019-12/caoa-abt122519.php. Post on Parkinson’s News Today: https://www.pdlink.org/tag/fuzzy-recurrence-plots/

48. M.D. Cirillo, R. Mirdell, F. Sjoberg, T.D. Pham, Time-independent prediction of burn depth by deep convolutional neural networks, Journal of Burn Care & Research, 40 (2019) 857-863.

49. T.D. Pham, Geostatistical simulation of medical images for data augmentation in deep learning, IEEE Access, 7 (2019) 68752-68763.

50. Q. Jin, Z. Meng, T.D. Pham, Q. Chen, L. Wei, R. Su, DUNet: A deformable network for retinal vessel segmentation, Knowledge-Based Systems, 178 (2019) 149-162.

51. M.D. Cirillo, R. Mirdell, F. Sjoberg, T.D. Pham, Tensor decomposition for color image segmentation of burn wounds, Scientific Reports, 9 (2019) 329.

52. T.D. Pham, Fuzzy weighted recurrence networks of time series, Physica A: Statistical Mechanics and its Applications, 513 (2019) 409-417.

53. T.D. Pham, Pattern analysis of computer keystroke time series in healthy control and early-stage Parkinson's disease subjects using fuzzy recurrence and scalable network features, Journal of Neuroscience Methods, 307 (2018) 194-202.

54. T.D. Pham, H. Yan, Spatial-dependence recurrence sample entropy, Physica A: Statistical Mechanics and its Applications, 494 (2018) 581-590.

55. T.D. Pham, H. Yan, Tensor decomposition of gait dynamics in Parkinson's disease, IEEE Trans Biomedical Engineering, 65 (2018) 1820-1827.

56. T.D. Pham, Texture classification and visualization of time series of gait dynamics in patients with neuro-degenerative diseases, IEEE Trans Neural Systems & Rehabilitation Engineering, 26 (2018) 188-196.

57. J. Liu, T.D. Pham, H. Yan, Z. Liang, Fuzzy mixed-prototype clustering algorithm for microarray data analysis, Neurocomputing, 276 (2018) 42-54.

58. T.D. Pham, H. Yan, A regularity statistic for images, Chaos, Solitons & Fractals, 106 (2018) 227-232.

59. T.D. Pham, M. Karlsson, C.M. Andersson, R. Mirdell, F. Sjoberg, Automated VSS-based burn scar assessment using combined texture and color features of digital images in error-correcting output coding, Scientific Reports, 7 (2017) 16744.

60. T.D. Pham, From fuzzy recurrence plots to scalable recurrence networks of time series, EPL (Europhysics Letters), 118 (2017) 20003.

61. T.D. Pham, Time-shift multiscale entropy analysis of physiological signals, Entropy, 19 (2017) 257. 

62. T.D. Pham, Validation of computer models for evaluating the efficacy of cognitive stimulation therapy, Wireless Personal Communications, 94 (2017) 301-314.

63. T.D. Pham, Y. Watanabe, M. Higuchi, H. Suzuki, Texture analysis and synthesis of malignant and benign mediastinal lymph nodes in patients with lung cancer on computed tomography, Scientific Reports, 7 (2017) 43209.

64. T.D. Pham, Fuzzy recurrence plots, EPL (Europhysics Letters), 116 (2016) 50008.

65. R. Su, C. Zhang, T.D. Pham, R. Davey, L. Bischof, P. Vallotton, D. Lovell, S. Hope, S. Schmoelzl, C. Sun, Detection of tubule boundaries based on circular shortest path and polar-transformation of arbitrary shape, Journal of Microscopy, 264 (2016) 127-142.

66. T.D. Pham, Quantifying visual perception of texture with fuzzy metric entropy, Journal of Intelligent & Fuzzy Systems, 31 (2016) 1089–1097.

67. T.D. Pham, The semi-variogram and spectral distortion measures for image texture retrieval, IEEE Trans Image Processing, 25 (2016) 1556-1565.

68. T.D. Pham, The Kolmogorov-Sinai entropy in the setting of fuzzy sets for image texture analysis and classification, Pattern Recognition, 53 (2016) 229-237.

69. X. Tan, C. Sun, T.D. Pham, Edge-aware filtering with local polynomial approximation and rectangle based weighting, IEEE Trans Cybernetics, 46 (2016) 2693-2705.

70. X. Tan, C. Sun, T.D. Pham, Stereo matching based on multi-direction polynomial model, Signal Processing: Image Communication, 44 (2016) 44-56.

71. X. Tan, C. Sun, K.Y.K. Wong, T.D. Pham, Guided image completion by confidence propagation, Pattern Recognition, 50 (2016) 210-222.

72. T.D. Pham, T. Abe, R. Oka, Y.F. Chen, Measures of morphological complexity of gray matter on magnetic resonance imaging for control age grouping, Entropy, 17 (2015) 8130-8151.

73. I. Arganda-Carreras, R. Turaga, D. Berger, D. Ciresan, A. Giusti, L. Gambardella, J. Schmidhuber, D. Laptev, S. Dwivedi, J. Buhmann, T. Liu, M.  Seyedhosseini, T. Tasdizen, L. Kamentsky, R. Burget, V. Uher, X. Tan, C. Sun, T.D. Pham, E. Bas, M.G. Uzunbas, A. Cardona, J. Schindelin, H. Seung, Crowdsourcing the creation of image segmentation algorithms for connectomics, Frontiers in Neuroanatomy, 9 (2015) 142.

74. T.D. Pham, Estimating parameters of optimal average and adaptive Wiener filters for image restoration with sequential Gaussian simulation, IEEE Signal Processing Letters, 22 (2015) 1950-1954.

75. X. Tan, C. Sun, X. Sirault, R. Furbank, T.D. Pham, Feature matching in stereo images encouraging uniform spatial distribution, Pattern Recognition, 48 (2015) 2530-2542.

76. T.D. Pham, M. Oyama-Higa, C.T. Truong, K. Okamoto, T. Futaba, S. Kanemoto, M. Sugiyama, L. Lampe, Computerized assessment of communication for cognitive stimulation for people with cognitive decline using spectral-distortion measures and phylogenetic inference, PLoS ONE, 10 (2015) e0118739.

77. C. Zhang, C. Sun, R. Su, T.D. Pham, Clustered nuclei splitting via curvature information and gray-scale distance transform, Journal of Microscopy, 259 (2015) 36-62.

78. T.D. Pham, Classification of complex biological aging images using fuzzy Kolmogorov-Sinai entropy, Journal of Physics D: Applied Physics, 47 (2014) 485402.

79. R. Su, C. Sun, C. Zhang, T.D. Pham, A novel method for dendritic spines detection based on directional morphological filter and shortest path, Computerized Medical Imaging and Graphics, 38 (2014) 793-802.

80. T.D. Pham, Spatial uncertainty modeling of fuzzy information in images for pattern classification, PLoS ONE, 9:8 (2014) e105075.

81. X. Tan, C. Sun, X. Sirault, R. Furbank, T.D. Pham, Stereo matching using cost volume watershed and region merging, Signal Processing: Image Communication, 29 (2014) 1232-1244.

82. T. Tsunoyama, T.D. Pham, T. Fujita, T. Sakamoto, Identification of intestinal wall abnormalities and ischemia by modeling spatial uncertainty in computed tomography imaging findings, Computer Methods and Programs in Biomedicine, 117 (2014) 30-39.

83. R. Su, C. Sun, C. Zhang, T.D. Pham, A new method for linear feature and junction enhancement in 2D images based on morphological operation, oriented anisotropic Gaussian function and Hessian information, Pattern Recognition, 47 (2014) 3193-3208.

84. T.D. Pham, The butterfly effect in ER dynamics and ER-mitochondrial contacts, Chaos, Solitons & Fractals, 65 (2014) 5-19.

85. T.D. Pham, Pattern recognition by active visual information processing in birds, Information Sciences, 270 (2014) 134-142.

86. T. Tsunoyama, T.D. Pham, T. Fujita, T. Sakamoto, Automated CT detection of intestinal abnormalities and ischemia for decision making in emergency medicine, BioMedical Engineering Online, 13: Suppl 1 (2014) S3.

87. T.D. Pham, Geostatistical entropy for texture analysis: an indicator kriging approach, Int. J. Intelligent Systems, 29 (2014) 253-265.

88. T.D. Pham, D.T.P. Le, J. Xu, D.T. Nguyen, R.G. Martindale, C.W. Deveney, Personalized identification of abdominal wall hernia meshes on computed tomography, Computer Methods and Programs in Biomedicine, 113 (2014) 153-161.

89. T.D. Pham, K. Ichikawa, Spatial chaos and complexity in the intracellular space of cancer and normal cells, Theoretical Biology and Medical Modelling, 10:62 (2013) DOI: 10.1186/1742-4682-10-62.

90. Y. Chen, T.D. Pham, Development of a brain MRI-based hidden Markov model for dementia recognition, BioMedical Engineering Online, 12: Suppl 1 (2013) S2.

91. I. Schwende, T.D. Pham, Pattern recognition and probabilistic measures for alignment-free sequence analysis, Briefings in Bioinformatics 2013; DOI: 10.1093/bib/bbt070.

92. C. Zhang, C. Sun, P. Vallotton, M. Fenech, T.D. Pham, Automatic nuclear bud detection using ellipse fitting, moving sticks or top-hat transformation, Journal of Microscopy, 252 (2013) 122-134.

93. T.D. Pham, C.T. Truong, M. Oyama-Higa, M. Sugiyama, Mental-disorder detection using chaos and nonlinear dynamical analysis of photoplethysmographic signals, Chaos, Solitons & Fractals, 51 (2013) 64–74.

94. C. Zhang, C. Sun, T.D. Pham, Segmentation of clustered nuclei based on concave curve expansion, Journal of Microscopy, 25 (2013) 57-67.

95. Y. Chen, T.D. Pham, Entropy and regularity dimension in complexity analysis of cortical surface structure in early Alzheimer's disease and aging, Journal of Neuroscience Methods, 215 (2013) 210-217.

96. T.D. Pham, Possibilistic nonlinear dynamical analysis for pattern recognition, Pattern Recognition, 46 (2013) 808–816.

97. B. Zhang, T.D. Pham, Serial fusion of random subspace ensemble for subcellular phenotype images classification, Int. J. Bioinformatics Research and Applications, 9 (2013) 386-406.

98. R. Su, C. Sun, T.D. Pham, Junction detection for linear structures based on Hessian, correlation and shape information, Pattern Recognition, 45 (2012) 3695­-3706.

99. T.D. Pham, Regularity dimension of sequences and its application to phylogenetic tree reconstruction, Chaos, Solitons & Fractals, 45 (2012) 879–887. 

100. T.D. Pham, Supervised restoration of degraded medical images using multiple-point geostatistics, Computer Methods and Programs in Biomedicine, 106 (2012) 201–209.

101. T.F. Ng, T.D. Pham, X. Jia, Feature interaction in subspace clustering using the Choquet integral, Pattern Recognition, 45 (2012) 2645-2660.

102. J. Liu, T.D. Pham, A spatially constrained fuzzy hyper-prototype clustering algorithm, Pattern Recognition, 45 (2012) 1759–1771.

103. J. Liu, T.D. Pham, FHC: The fuzzy hyper-prototype clustering algorithm, Int. J. Knowledge-Based and Intelligent Engineering Systems, 16 (2012) 35-47.

104. B. Wang, T.D. Pham, MRI-based age prediction using hidden Markov models, J.  Neuroscience Methods, 199 (2011) 140– 145.

105. J. Liu, T.D. Pham, Fuzzy clustering for microarray data analysis: A review, Current Bioinformatics, 6 (2011) 427-443.

106. B. Zhang, T.D. Pham, Phenotype recognition with combined features and random subspace classifier ensemble, BMC Bioinformatics 2011, 12:128 (doi:10.1186/1471-2105-12-128).

107. D. Beck, S. Ayers, J. Wen, M. Brandl, T.D. Pham, P. Webb, C.-C. Chang, X. Zhou, Integrative analysis of next generation sequencing for small non-coding RNAs and transcriptional regulation in myelodysplastic syndromes, BMC Medical Genomics 2011, 4:19 (doi:10.1186/1755-8794-4-19).

108. T.D. Pham, K. Berger, Automated detection of white matter changes in elderly people using fuzzy, geostatistical, and information combining models, IEEE Trans Information Technology in Biomedicine, 15 (2011) 242-250.

109. T.D. Pham, F. Salvetti, B. Wang, M. Diani, W. Heindel, S. Knecht, H. Wersching, B.T. Baune, K. Berger, The hidden-Markov brain: comparison and inference of white matter hyperintensities on magnetic resonance imaging (MRI), Journal of Neural Engineering, 8 (2011) 016004  (doi:10.1088/1741-2560/8/1/016004).

110. T.D. Pham, Fuzzy posterior-probabilistic fusion, Pattern Recognition, 44 (2011) 1023–1030.

111. T.D. Pham, H.Z. Elfiqi, S. Knecht, H. Wersching, B.T. Baune, K. Berger, Structural simplexity of the brain, J.  Neuroscience Methods, 188 (2010) 113–126.

112. T.D. Pham, GeoEntropy:  A measure of complexity and similarity, Pattern Recognition, 43 (2010) 887-896.

113. T.D. Pham, D. Beck, M. Brandl, Identification of protein biomarkers using geostatistics and block-error matching strategy, Trans.  Mass-Data Analysis of Images and Signals, 1:2 (2009) 178-197.

114. C. To, T.D. Pham, Analysis of massive data in biology using hyperplane-based genetic algorithms, Trans.  Mass-Data Analysis of Images and Signals, 1:1 (2009) 76-88.

115. T.D. Pham, M. Brandl, D. Beck, Fuzzy declustering-based vector quantization, Pattern Recognition, 42 (2009) 2570-2577.

116. T.D. Pham, C. Muller, D.I. Crane, Fuzzy scaling analysis of a mouse mutant with brain morphological changes, IEEE Trans Information Technology in Biomedicine, 13:4 (2009) 629-635.

117. T.D. Pham, U. Eisenblätter, B.T. Baune, K. Berger, Preprocessing film-copied MRI for studying brain morphological changes, J.  Neuroscience Methods, 180:2 (2009) 352-362.

118. D. Yu, T.D. Pham, X. Zhou, Analysis and recognition of touching cell images based on morphological structures, Computers in Biology and Medicine, 39 (2009) 27-39.

119. D. Yu, T.D. Pham, X. Zhou, S.T.C. Wong, Recognition and analysis of cell nuclear phases for high content screening based on morphological features, Pattern Recognition, 42 (2009) 498-508.

120. D. Yu, T.D. Pham, H. Yan, J. Jin, S. Luo, D.I. Crane, Image processing and reconstruction of cultured neuron skeletons, Int. J. Hybrid Intelligent Systems, 5:4 (2008) 179-196.

121. T.D. Pham, Fuzzy fractal analysis of molecular imaging data, Special Issue on “Computational Systems Biology”, Proceedings of the IEEE, 96 (2008) 1332-1347. 

122. T.D. Pham, H. Wang, X. Zhou, D. Beck, M. Brandl,  G. Hoehn, J. Azok, M.-L. Brennan, S. L. Hazen, K. Li, S.T.C. Wong, Computational prediction models for early detection of risk of cardiovascular events using mass spectrometry data, IEEE Trans Information Technology in Biomedicine, 12 (2008) 636-643. 

123. T.D. Pham, Computational prediction models for cancer classification using mass spectrometry data, Int. J. Data Mining and Bioinformatics, 2 (2008) 405-422. 

124. D. Yu, T.D. Pham, H. Yan, B. Zhang, D.I. Crane, Segmentation of cultured neurons using logical analysis of grey difference, J. Neuroscience Methods, 166 (2007) 125–137.

125. T.D. Pham, D.T. Tran, X. Zhou, and S.T.C. Wong, A microscopic image classification system for high-throughput cell-cycle screening, Int. J.  Intelligent Computing in Medical Sciences and Image Processing, 1:1 (2007) 67-77.

126. H. Yan, T.D. Pham, Spectral estimation techniques for DNA sequence and microarray data analysis, Current Bioinformatics, 2:2 (2007) 145-156. 

127. T.D. Pham, D.T. Tran, X. Zhou, Fuzzy information fusion of classification models for high-throughput image screening of cancer cells in time-lapse microscopy, Int. J.  Knowledge-Based and Intelligent Engineering Systems, 11:4 (2007) 237-246.

128. T.D. Pham, Spectral distortion measures for biological sequence comparisons and database searching, Pattern Recognition, 40:2 (2007) 516-529.

129. T.D. Pham, D. Beck, H. Yan, Spectral pattern comparison methods for cancer classification based on microarray gene expression data, IEEE Trans. Circuits and Systems I: Fundamental Theory and Applications, special issue on Advances on Life Science Systems, 53:11 (2006) 2425-2430. 

130. T.D. Pham, D. T. Tran, X. Zhou, S.T.C. Wong, Integrated algorithms for image analysis and identification of nuclear division for high-content cell-cycle screening, Int. J.  Computational Intelligence and Applications, 6:1 (2006) 21-43.

131. H. Yan, T. Pham, Spectral similarity for analysis of DNA microarray time-series data, Int. Journal of Data Mining and Bioinformatics, 1:2 (2006) 150-161.

132. T.D. Pham, LPC cepstral distortion measure for protein sequence comparison, IEEE Trans. NanoBioscience, 5:2 (2006) 83-88. 

133. T.D. Pham, Handling missing DNA microarray data by kriging estimators, Int. J. Bioinformatics Research and Applications, 2:2 (2006) 177-192. 

134. T.D. Pham, C. Wells, D.I. Crane, Analysis of microarray gene expression data, invited paper, Current Bioinformatics, 1:1 (2006) 37-53. 

135. T.D. Pham, J. Zuegg, A probabilistic measure for alignment-free sequence comparison, Bioinformatics, 20:18 (2004) 3455-3461. 

136. T.D. Pham, D. Crane, T.H. Tran, T.H. Nguyen, Extraction of fluorescent cell puncta by adaptive fuzzy segmentation, Bioinformatics, 20:14 (2004) 2189-2196. 

137. T.D. Pham, Unconstrained logo detection in document images, Pattern Recognition, 36:2 (2003) 3023-3025. 

138. T.D. Pham, Perception-based hidden Markov models: A theoretical framework for data mining and knowledge discovery, Soft Computing, 6:5 (2002) 400-405. 

139. T.D. Pham, An image restoration by fusion, Pattern Recognition, 34:12 (2001) 2403-2411. 

140. T.D. Pham, Computing with words in formal methods, Int. J. Intelligent Systems, 15:8 (2000) 801-810. 

141. T.D. Pham, M. Wagner, Image enhancement by kriging and fuzzy sets, Int. J. Pattern Recognition and Artificial Intelligence, 14:8 (2000) 1025-1038. 

142. T.D. Pham, M. Wagner, Similarity normalization for speaker verification by fuzzy fusion, Pattern Recognition, 33:2 (2000) 309-315. 

143. T.D. Pham, M. Wagner, Speaker verification with fuzzy fusion and genetic optimization, Int. J. Advanced Computational Intelligence (Special Issue on Learning in Intelligent Algorithms and Systems Design), 3:6 (1999) 451-456. 

144. T.D. Pham, M. Wagner, Ambiguity-reduction in speaker identification using relaxation label­ing process, Pattern Recognition, 32:7 (1999) 1249-1254. 

145. T.D. Pham, H. Yan, Color image segmentation using fuzzy integral and mountain clustering, Fuzzy Sets and Systems, 107 (1999) 121-130. 

146. A.R. Mirhosseini, H. Yan, K.M. Lam, T. Pham, Human face image recognition: An evidence aggregation approach, Computer Vision & Image Understanding, 71:2 (1998) 213-230. 

147. T.D. Pham, Reply to comment by Z. Sen, I. Sonmez, and H. Tath on “Grade estimation using fuzzy-set algorithms”, Mathematical Geology, 30:8 (1998) 1039-1042.

148. T.D. Pham, M. Wagner, A geostatistical model for linear prediction analysis of speech, Pattern Recognition, 31:12 (1998) 1981-1991. 

149. T.D. Pham, H. Yan, An effective algorithm for the segmentation of digital plane curves – The isoparametric formulation, Pattern Recognition Letters, 19 (1998) 171-176. 

150. T.D. Pham, H. Yan, A kriging fuzzy integral, Information Sciences, 98 (1997) 157-173. 

151. T.D. Pham, H. Yan, A quasi-linear fuzzy measure of multi-attributes, Fuzzy Sets and Systems, 90 (1997) 255-266. 

152. T.D. Pham, Grade estimation using fuzzy-set algorithms, Mathematical Geology, 29:2 (1997) 291­305. 

153. S. Valliappan, T.D. Pham, Elasto-plastic finite element analysis with fuzzy parameters, Int.  J. Numerical Methods in Engineering, 38 (1995) 531-548. 

154. T.D. Pham, S. Valliappan, A least squares model for fuzzy rules of inference, Fuzzy Sets and Systems, 64 (1994) 207-212. 

155. S. Valliappan, T.D. Pham, Fuzzy finite element analysis of a foundation on an elastic soil medium, Int. J. Numerical and Analytical Methods in Geomechanics, 17 (1993) 771-789. 

156. T.D. Pham, S. Valliappan, Constructing the membership function of a fuzzy set with objective and subjective information, Microcomputers in Civil Engineering, 8 (1993) 75-82. (New journal title: Computer-Aided Civil and Infrastructure Engineering, Wiley). 

157. S. Valliappan, T.D. Pham, V. Murti, J. Franklin, Fuzzy logic for automatic finite element mesh generator, Microcomputers in Civil Engineering, 8 (1993) 1-8.  (New journal title: Computer-Aided Civil and Infrastructure Engineering, Wiley). 

PAPERS IN REFEREED CONFERENCE PROCEEDINGS

1. T.D. Pham, Textures and networks of healthy and pathological voice signals, First IEEE International Conference on Artificial Intelligence for Medicine, Health, and Care (AIMHC 2024, February 5-7, 2024, California, USA) pp. 14-15, 2024. DOI 10.1109/AIMHC59811.2024.00009

2. W. Suliman, V. Ravi, T.D. Pham, A retrospective study on classifying gait signals using entropy measures, 2023 IEEE Region 10 Conference (IEEE TENCON 2023, 31 October - 3 November 2023, Chiang Mai, Thailand) pp. 948-953, 2023.

3. T.D. Pham, Efficient deep learning for pathological speech recognition, 2023 IEEE Conference on Artificial Intelligence (IEEE CAI, 5-6 June 2023, Santa Clara, CA, USA) pp. 103-104, 2023.

4. T.D. Pham, X.F. Sun, Wavelet scattering of RhoB-expressed deep-learning features for rectal cancer prognosis, 2023 IEEE International Symposium on Biomedical Imaging (ISBI 2023, 18-21 April 2023, Cartagena de Indias, Colombia), pp. 1-4. DOI: 10.1109/ISBI53787.2023.10230417.

5. T.D. Pham, Visual concurrent analysis of gait patterns among healthy young, old adults, and patients with Parkinson's disease, 2022 IEEE International Conference on Bioinformatics and Biomedicine (IEEE-BIBM 2022, 6-9 December 2022, Las Vegas, USA) pp. 2674-2681, 2022. DOI: 10.1109/BIBM55620.2022.9995627.

6. T.D. Pham, Classification of ECG signals of heart beats using TF-TS LSTM with augmented fuzzy recurrence eigenvalues, 2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP 2022, 26-29 June 2022, Nafplio, Greece) pp. 1-5, 2022, DOI: 10.1109/IVMSP54334.2022.9816174.

7. W. Suliman, V. Ravi, B. Luo, X.F. Sun, T.D. Pham, Convolutional neural networks and support vector machines for five-year survival analysis of metastatic rectal cancer, International Joint Conference on Neural Networks (IJCNN 2022, 18-23 July 2022, Padua, Italy) pp. 1-8, doi: 10.1109/IJCNN55064.2022.9892935.

8. T.D. Pham, Deep learning of recurrence texture in physiological signals, 20th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2021, 01-03 December 2021, Milan, Italy) Lecture Notes in Artificial Intelligence, vol. 13196, pp. 503-514, 2022.

9. T.D. Pham, Fusion of momentary moods in major depression with fuzzy recurrence analysis and tensor decomposition, International Conference on Electrical, Computer and Energy Technologies (ICECET'21, Cape Town, South Africa, 09-10 December 2021) pp. 1-6, 2021, DOI: 10.1109/ICECET52533.2021.9698467. 

10. T.D. Pham, Classification of gait in Parkinson's disease using single sensors, International Conference on Electrical, Computer and Energy Technologies (ICECET'21, Cape Town, South Africa, 09-10 December 2021) pp. 1-5, 2021, DOI: 10.1109/ICECET52533.2021.9698524.

11. T.D. Pham, F.Y. Al Anezi, Fuzzy cross recurrence analysis and tensor decomposition of major-depression time-series data, 3rd ACM International Conference on Data Science, E-learning and Information Systems (Data’21, 5-7 April 2021, Petra, Jordan) ACM, New York, NY, USA, pp. 28-34, 2021. DOI: 10.1145/3460620.3460626.

12. T.D. Pham, Classification of benign and metastatic lymph nodes in lung cancer with deep learning, 20th IEEE Conference on Bioinformatics and Bioengineering (BIBE-2020, 26-28 October 2020, Cincinnati, OH, USA), pp. 728-733, 2020.

13. T.D. Pham, Visual computing of causality in personalized depression, 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2020, 20-24 July 2020, Montréal, Canada) pp. 5510-5513, 2020.  

14. T.D. Pham, The recurrence dynamics of personalized depression, Proceedings of the Australasian Computer Science Week Multiconference (ACSW 2020, 04-06 February 2020, Melbourne, VIC, Australia) ACM, New York, NY, USA, 8 pages, 2020.

15. T.D. Pham, C.W. Fan, H. Zhang, X.F. Sun, Deep learning of p73 biomarker expression in rectal cancer patients, 2019 International Joint Conference on Neural Networks (IJCNN 2019, 14-19 July 2019, Budapest, Hungary) pp. 1-8, 2019.  DOI: 10.1109/IJCNN.2019.8852245.

16. T.T.T. Pham, H.R. Deniz, T.D. Pham, Tensor decomposition of non-EEG physiological signals for visualization and recognition of human stress, 11th Int. Conf. Bioinformatics and Biomedical Technology (ICBBT’19, 29-31 May 2019, Stockholm, Sweden) ACM, New York, NY, USA, pp. 132-136, 2019. DOI: https://doi.org/10.1145/3340074.3340096.

17. T.D. Pham, Quantification of white matter lesions on brain MRI with 2D fuzzy weighted recurrence networks, 9th International IEEE/EMBS Conference on Neural Engineering (NER’19, 20-23 March 2019, San Francisco, CA, USA) pp. 110-113, 2019.

18. T.D. Pham, M. Oyama-Higa, Nonlinear dynamics analysis of short-time photoplethysmogram in Parkinson's disease, 2018 IEEE Int. Conf. Fuzzy Systems (FUZZ-IEEE 2018, 08-13 July 2018, Rio de Janeiro, Brazil) pp. 1749-1754, 2018.

19. T.D. Pham, Pattern analysis and classification of blood oxygen saturation signals with nonlinear dynamics features, 2018 IEEE Int. Conf. Biomedical and Health Informatics (BHI 2018, 4-7 March 2018, Las Vegas, Nevada, USA), pp. 112-115, 2018.

20. T.D. Pham, Complementary features for radiomic analysis of malignant and benign mediastinal lymph nodes, 2017 IEEE Int. Conf. Image Processing (IEEE ICIP 2017, 17-20 September 2017, Beijing, China) pp. 3849-3853, 2017.

21. T.D. Pham, Scaling of texture in training autoencoders for classification of histological images of colorectal cancer, Fourteenth International Symposium on Neural Networks (ISNN 2017, 21-23 June 2017, Sapporo, Japan), ISNN 2017, Part II, LNCS 10261, pp. 524-532, 2017.

22. T.D. Pham, Entropy rates of physiological aging on microscopy, Proc. 2016 IEEE Symposium on Computational Intelligence in Big Data (IEEE CIBD'16, 6-9 December 2016, Athens, Greece), 2016 IEEE Symposium Series on Computational Intelligence (SSCI 2016), pp. 1-5, DOI: 10.1109/SSCI.2016.7849867.

23. T.D. Pham, Noise-added texture analysis, XXI IberoAmerican Congress on Pattern Recognition (CIARP 2016, 8-11 November 2016, Lima, Peru), CIARP 2016, LNCS 10125, pp. 93-100, 2017.

24. X. Zhou, G. Zhong, L. Qi, J. Dong, T.D. Pham, J. Mao, Surface height map estimation from a single image using convolutional neural networks, SPIE 8th Int. Conf. Graphic and Image Processing (ICGIP 2016, 29-31 October 2016, Tokyo, Japan) 1022524 (February 8, 2017); doi:10.1117/12.2266479.

25. G. Zhong, H. Yao, Y. Liu, C. Hong, T.D. Pham, Classification of photographed document images based on deep-learning features, SPIE 8th Int. Conf. Graphic and Image Processing (ICGIP 2016, 29-31 October 2016, Tokyo, Japan) 102250X (February 8, 2017); doi:10.1117/12.2266984.

26. T.D. Pham, Measures of spatial distortion using kriging, Proc. 8th IEEE Int. Conf. Intelligent Systems (IEEE-IS’16, 04-06 September 2016, Sofia, Bulgaria), pp. 438-442, 2016.

27. T.D. Pham, Enhancing texture characteristics with synthesis and noise for image retrieval, Proc. 8th IEEE Int. Conf. Intelligent Systems (IEEE-IS’16, 04-06 September 2016, Sofia, Bulgaria), pp. 433-437, 2016.

28. T.D. Pham, The multiple-point variogram of images for robust texture classification, Proc. 41st IEEE Int. Conf. Acoustics, Speech and Signal Processing (ICASSP 2016, 20-25 March 2016, Shanghai, China), pp. 1303-1307, 2016.

29. T.D. Pham, Measure of texture dynamics with fuzzy metric entropy, Proc. 12th Int. Conf. Fuzzy Systems and Knowledge Discovery (FSKD’15, 15-17 Aug 2015, Zhangjiajie, China), pp. 417-422, 2015.

30. T.D. Pham, M. Oyama-Higa, Photoplethysmography technology and its feature visualization for cognitive stimulation, Proc. 2015 IEEE Int. Conf. Industrial Technology (IEEE-ICIT 2015, 17-19 March 2015, Saville, Spain), pp. 1735-1740, 2015.

31. T.D. Pham, Dynamic-time-warping analysis of feature-vector reliability, 2015 Int. Conf. Information Science and Applications (24-26 February 2015, Pattaya, Thailand), Springer LNEE 339, pp. 235-241, 2015.

32.  T.C. Thang, H.T. Tran, V.D. Trong, D.V. Nguyen, H.T. Le, T.D. Pham, Design and implementation of an e-Health system for depression detection, 2015 IEEE Int. Conf. Consumer Electronics (IEEE-ICCE 2015, 9-12 January 2015, Las Vegas, NV, USA), pp. 74-75, 2015.

33. T.D. Pham, Modeling spatial uncertainty of imprecise information in images, Proc. The Asia-Pacific Signal and Information Processing Association 2014 (APSIPA2014, 9-12 December 2014, Siem Reap, Cambodia), ISBN 978-616-361-823-8.

34. T.D. Pham, Detecting mitochondria in intracellular images with nonstationary indicator kriging, IEEE TENCON 2014 (22-25 October 2014, Bangkok, Thailand), paper index 00018.

35. T.D. Pham, K. Ichikawa, Characterization of cancer intracellular space using the K-S entropy for images, IEEE TENCON 2014 (22-25 October 2014, Bangkok, Thailand), paper index 00178.

36. X. Tan, C. Sun, T.D. Pham, Soft cost aggregation with multi-resolution fusion, European Conference on Computer Vision 2014 (ECCV 2014, 6-12 September 2014, Zurich, Switzerland), Part V, LNCS 8693, pp. 17–32, 2014.

37. T.D. Pham, T. Tsunoyama, T.C. Thang, T. Fujita, T. Sakamoto, Image classification of bowel abnormalities and ischemia, 2014 IEEE Int. Conf. Image Processing (ICIP 2014, 27-30 October 2014, Paris, France), pp. 2764-2768.

38. T.D. Pham, Image classification with indicator kriging error comparison, Int. Conf. Image and Signal Processing (ICISP 2014, June 30 – July 02, 2014, Cherbourg, France), LNCS 8509, pp. 433–440, 2014.

39. T.D. Pham, Nonstationary mapping of spatial uncertainty for medical image classification, Int. Conf. Medical Biometrics (ICMB 2014, May 30 – June 01, 2014, Shenzhen, China) pp. 164-168, 2014.

40. X. Tan, C. Sun, T.D. Pham, Multipoint filtering with local polynomial approximation and range guidance, 27th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014, 24-27 June 2014, Columbus, Ohio, USA) pp. 2941-2948, 2014. 

41. T.D. Pham, The chaotic behavior of the endoplasmic-reticulum network in time-lapse microscopy images, IEEE-BIBM-2013 Int. Workshop on Bioinformatics in Biomedical Imaging (18-21 December 2013, Shanghai, China) pp. 22-25, 2013.

42. T.D. Pham, J. Golledge, Pattern analysis of imaging markers in abdominal aortic aneurysms, 6th Int. Conf. BioMedical Engineering and Informatics (BMEI 2013, 16-18 December 2013, Hangzhou, China) pp. 154-159, 2013.

43. T.D. Pham, Bird-like information processing for AI-based pattern recognition, 12th Mexican Int. Conf. Artificial Intelligence (MICAI 2013, 24-30 November 2013, Mexico City, Mexico) pp. 157-163, 2013.

44. T.D. Pham, Automated identification of mitochondrial regions in complex intracellular space by texture analysis, SPIE 5th Int. Conf. Graphics and Image Processing (ICGIP 2013, 26-27 October 2013, Hong Kong), Proc. SPIE 90690G (January 10, 2014).  DOI:10.1117/12.2050102.

45. Y. Kurosawa, T. Takezawa, T.D. Pham, Psychomime classification using similarity measures and fuzzy c-means, First Int. Aizu Conf. Biomedical Informatics and Technology (ACBIT 2013, Aizu-Wakamatsu, Japan, September 16-17, 2013), Springer Communications in Computer and Information Science, vol. 404, pp. 194-206.

46. Y. Chen, M. Oyama-Higa, T.D. Pham, Identification of mental disorders by hidden Markov modelling of photoplethysmograms, First Int. Aizu Conf. Biomedical Informatics and Technology (ACBIT 2013, Aizu-Wakamatsu, Japan, September 16-17, 2013), Springer Communications in Computer and Information Science, vol. 404, pp. 29-39.

47. I. Schwende, T.D. Pham, K. Ichikawa, Nuclear boundary and pore detection in SEM images, First Int. Aizu Conf. Biomedical Informatics and Technology (ACBIT 2013, Aizu-Wakamatsu, Japan, September 16-17, 2013), Springer Communications in Computer and Information Science, vol. 404, pp. 235-247.

48. T. Abe, Y. Chen, T.D. Pham, Chaos analysis of brain MRI for studying mental disorders, First Int. Aizu Conf. Biomedical Informatics and Technology (ACBIT 2013, Aizu-Wakamatsu, Japan, September 16-17, 2013), Springer Communications in Computer and Information Science, vol. 404, pp. 257-270.

49. T.D. Pham, K-S entropy of images, 20th Int. Conf. Systems, Signals, and Image Processing (07-09 July 2013, Bucharest, Romania) pp. 15-18, 2013. 

50. C. Zhang, C. Sun, R. Davey, R. Su, L. Bischof, P. Vallotton, D. Lovell, S. Hope, S. Lehnert, T.D. Pham, Tubule detection in testis images using boundary weighting and circular shortest path, 35th IEEE EMBS Conf. Engineering in Medicine and Biology (03-07 July 2013, Osaka, Japan) pp. 3319-3322, 2013.

51. T.D. Pham, K. Ichikawa, Characterization of cancer and normal intracellular images by the power law of a fuzzy partition functional, Int. Conf. Image Analysis and Recognition (ICIAR 2013, June 26-28, 2013, Póvoa de Varzim, Portugal) LNCS 7950, pp. 597–604, 2013.

52. Y. Chen, T.D. Pham, Analysis of MRI-based cortical surface structure complexity in dementia by sample entropy, 2013 IEEE Symposium Series on Computational Intelligence (IEEE-CIS 2013, 15-19 April 2013, Singapore) pp. 189-192, 2013.

53. N. Nguyen-Thanh, T.D. Pham, K. Ichikawa, Segmentation of mitochondria in intracellular space, 2013 IEEE Symposium Series on Computational Intelligence (IEEE-CIS 2013, 15-19 April 2013, Singapore) pp. 218-221, 2013.

54. T.D. Pham, T.C. Thang, M. Oyama-Higa, H.X. Nguyen, H. Saji, M. Sugiyama, Chaos and nonlinear time-series analysis of finger pulse waves for depression detection, Biosignals 2013 (11-14 February 2013, Barcelona, Spain) pp. 298-301, 2013. 

55. T.D. Pham, T.C. Thang, M. Oyama-Higa, Toward the development of a cost-effective e-depression detection system, 2012 Int.  Conf. Computerized Healthcare (ICCH 2012, 17-18 December 2012, Hong Kong) pp. 23-28, 2012.

56. T.D. Pham, N. Nguyen-Thanh, T.C. Thang, K. Ichikawa, Chaotic behavior in intracellular space: an implication for simulation and modeling of cancer, European Modelling Symposium 2012 (EMS2012, 14-16 November 2012, Malta) pp. 143-147, 2012.

57. T.D. Pham, D. Vo, N. Nguyen-Thanh, T.C. Thang, K. Ichikawa, How complex is cancer intracellular signaling space in FIB-SEM Images? European Modelling Symposium 2012 (EMS2012, 14-16 November 2012, Malta) pp. 139-142, 2012.

58. T.D. Pham, Image and signal analysis for personalized modeling in medicine and mental health, Summer School—Advanced Aspects of Theoretical Electrical Engineering 2012 (Sozopol’2012, 07-09 September 2012, Sozopol, Bulgaria), pp. 14-19, 2012, invited paper.

59. X. Tan, C. Sun, X. Sirault, R. Furbank, T.D. Pham, Cross image inference scheme for stereo matching, 11th Asian Conference on Computer Vision  (ACCV 2012, Daejeon, Korea, 5-9 November 2012) LNCS 7727 (2013) 217-230.

60. X. Tan, C. Sun, X. Sirault, R. Furbank, T.D. Pham, Tree structural watershed for stereo matching, 27th International Conference on Image and Vision Computing New Zealand (IVCNZ'12, 26-28 November 2012, Dunedin, New Zealand) pp. 340-345, 2012.

61. R. Su, C. Zhang, C. Sun, T.D. Pham, Linear feature enhancement based on morphological operation and Gabor function, 27th International Conference on Image and Vision Computing New Zealand (IVCNZ'12, 26-28 November 2012, Dunedin, New Zealand) pp. 91-96, 2012.

62. C. Zhang, R. Su, C. Sun, T.D. Pham, Segmentation of clustered nuclei based on curvature weighting, 27th International Conference on Image and Vision Computing New Zealand (IVCNZ'12, 26-28 November 2012, Dunedin, New Zealand) pp. 49-54, 2012.

63. T.D. Pham, D.T.P. Le, J. Xu, D.T. Nguyen, R.G. Martindale, C.W. Deveney, Personalized hernia mesh identification, 8th International Seminar on Medical Information Processing and Analysis (12-15 November 2012, San Cristóbal, Venezuela), pp. 31-39, 2012 (ISBN: 978-980-6300-72-9).

64. X. Tan, C. Sun, X. Sirault, R. Furbank, T.D. Pham. Feature correspondence with even distribution, Digital Image Computing: Techniques and Applications (3-5 December 2012, Perth, Australia), 7 pages, 2012.

65. R. Su, C. Sun, T.D. Pham, Dendritic spines detection based on directional morphological filter and shortest path, 34th IEEE EMBS Conf. Engineering in Medicine and Biology (August 28 - September 01, 2012, San Diego, California, USA), pp. 5343-5346, 2012.

66. T.D. Pham, Regularity dimension of medical images, 16th Inter. Conf. Knowledge-Based and Intelligent Information & Engineering Systems (KES-2012, 10-12 September 2012, San Sebastian, Spain), in: Advances in Knowledge-Based and Intelligent Information and Engineering Systems, vol. 232, pp. 314-323, 2012.

67. T.D. Pham, Image texture analysis using geostatistical information entropy, 6th IEEE Inter. Conf. Intelligent Systems (IS’12, September 6-8, 2012, Sofia, Bulgaria), pp. 353-356, 2012.

68. T.D. Pham, Kriging-based possibilistic entropy of biosignals, 20th European Signal Processing Conference (EUSIPCO-2012, August 27-31, 2012, Bucharest, Romania), pp. 1816-1820, 2012.

69. J. Xu, T.D. Pham, Robust impulse-noise filtering for biomedical images using numerical interpolation, Int. Conf. Image Analysis and Recognition, (ICIAR 2012, June 25-27, 2012, Aveiro, Portugal), LNCS 7325, pp. 146-155, 2012.

70. T.D. Pham, Uncertainty in multiscale possibilistic nonlinear dynamical analysis of biosignals, Proc.  Third IEEE Biosignals and Biorobotics (BRC 2012, 9-11 January 2012, Manaus, Brazil), 4 pages, DOI: 10.1109/BRC.2012.6222196.

71. C. Zhang, C. Sun, T.D. Pham, Clustered nuclei splitting using curvature information, DICTA 2011 (Noosa, Queensland, 6-8 December 2011, Australia) pp. 352-357, 2011.

72. B. Wang, T.D. Pham, HMM-based brain age interpolation using kriging estimator, Seventh IEEE Int. Symp. Image and Signal Processing and Analysis (ISPA 2011, 4-6 September 2011, Dubrovnik, Croatia) pp. 704-708, 2011.

73. J-W. Xu, T.D. Pham, X. Zhou, A double thresholding method for cancer stem cell detection, Seventh IEEE Int. Symp. Image and Signal Processing and Analysis (ISPA 2011, 4-6 September 2011, Dubrovnik, Croatia) pp. 695-699, 2011.

74. F. Salvetti, T.D. Pham, On improving the inference of white matter hyperintensities on magnetic resonance imaging, Seventh IEEE Int. Symp. Image and Signal Processing and Analysis (ISPA 2011, 4-6 September 2011, Dubrovnik, Croatia) pp. 690-694, 2011.

75. T.D. Pham, Possibilistic entropy: A new approach for nonlinear dynamical analysis of biosignals, 15th Int. Conf.  Knowledge-Based & Intelligent Information & Engineering Systems – KES2011 (12-14 September 2011, Kaiserslautern, Germany) LNAI 6881, pp. 466-473, 2011.

76. D. Yu, T.D. Pham, V. Nägerl, Knowledge-based morphology quantification of STED dendritic spine images, 5th European Conf. of International Federation for Medical and Biological Engineering  (IFMBE MBEC 2011, Budapest, Hungary, 14-18 September 2011)  pp. 1210-1213, 2011.

77. B. Wang, T.D. Pham, Estimating neuronal ageing with hidden Markov models, 2011 Int. Symp. Computational Models for Life Sciences (CMLS-11, 11-13 October 2011, Toyama City, Japan) pp. 110-117, 2011.

78. R. Su, C. Sun, T.D. Pham, Junction detection for linear structures, 2011 Int. Symp. Computational Models for Life Sciences (CMLS-11, 11-13 October 2011, Toyama City, Japan) pp. 29-36, 2011.

79. X. Zhou, Y. Wang, H. Wang, T.D. Pham, K. Li, Biomarker motif discovery by integrating mass spectrometry and protein-protein interaction network, 2011  Int. Symp. Computational Models for Life Sciences (CMLS-11, 11-13 October 2011, Toyama City, Japan) pp. 225-233, 2011.

80. D. Beck, M. Brandl, T.D. Pham, C.-C. Chang, X. Zhou. In-silico identification of micro-loops in myelodysplastic syndromes, 2011 Int. Symp. Computational Models for Life Sciences (CMLS-11, 11-13 October 2011, Toyama City, Japan) pp. 263-271, 2011.

81. M. Brandl, D. Beck, T.D. Pham, Application of fuzzy c-means and joint-feature-clustering to detect redundancies of image-features in drug combinations studies of breast cancer, 2011 Int. Symp. Computational Models for Life Sciences (CMLS-11, 11-13 October 2011, Toyama City, Japan) pp. 65-72, 2011.

82. Y. Xiao, T.D. Pham, J. Chang, X. Zhou, Symmetry-based presentation for stem-cell image segmentation, First IEEE Int. Conf. Computational Advances in Bio and Medical Sciences (ICCABS 2011, 3-5 February 2011, Orlando, Florida) pp. 196-201, 2011.

83. C.C. To, T.D. Pham, Complexity analysis of mass spectrometry data for disease classification using GA-based multiscale entropy, Proc. Biosignals 2011 (26-29 January 2011, Rome, Italy)  pp. 5-14, 2011 (Full paper). BIOSIGNALS 2011 received 149 submissions, of which 8% were accepted as full papers.

84. D. Yu, J.S. Jin, S. Luo, W. Lai, M. Park, T.D. Pham, Shape analysis and recognition based on skeleton and morphological structure,  Proc. Seventh Int. Conf.  Computer Graphics, Imaging and Visualization (7-10 August 2010, Sydney, Australia) pp. 118-123, 2010.

85. J. Liu, T.D. Pham, W. Wen, P. Sachdev, Spatially constrained fuzzy hyper-prototype clustering with application to brain tissue segmentation,  2010 IEEE Int.  Conf.  Bioinformatics & Biomedicine (IEEE-BIBM 2010, 18-21 December 2010, Hong Kong) pp. 397-400, 2010.

86. C. Zhang,  C. Sun, T.D. Pham, P. Vallotton, M. Fenech, Detection of nuclear buds based on ellipse fitting, (DICTA 2010, 1-3 December 2010, Sydney, Australia) pp. 178-183, 2010.

87. T.D. Pham, Brain lesion detection in MRI with fuzzy and geostatistical models, Proc. 32nd Annual Int.  Conf. IEEE Engineering in Medicine and Biology (EMBC'10, Buenos Aires, Argentina, 01-04 September 2010) pp. 3150-3153, 2010.

88. T.D. Pham, Medical image restoration using multiple-point geostatistics, Proc. 3rd Int. Conf. Biomedical Engineering and Informatics (BMEI 2010, 16-18 October 2010, Yantai, China) pp. 371-374, 2010.

89. Y. Xiao, T.D. Pham, X. Jia, X. Zhou, H. Yan, Correlation based cluster-space transform for major adverse cardiac event prediction, Proc. 2010 IEEE Int. Conf.  Systems, Man, and Cybernetics (IEEE-SMC 2010, 10-13 October 2010, Istanbul, Turkey) pp. 2003-2007, 2010.

90. T.D. Pham, Fusing fuzzy and probabilistic memberships for white matter lesion detection in MRI of the brain, Proc. 2010 IEEE Int. Conf.  Systems, Man, and Cybernetics (IEEE-SMC 2010, 10-13 October 2010, Istanbul, Turkey) pp. 2124-2128, 2010.

91. J. Liu, T.D. Pham, Fuzzy hyper-prototype clustering, Proc. 14th Int. Conf.  Knowledge-Based and Intelligent Information & Engineering Systems (KES’2010, 8-10 September 2010, Cardiff, Wales, UK) pp. 379-389, 2010.

92. T. Ng, T.D. Pham, C. Sun, Automated feature weighting in fuzzy declustering-based vector quantization, Proc.  2010 Int.  Conf. Pattern Recognition (ICPR 2010, 23-26 August 2010, Istanbul, Turkey) pp. 696-699, 2010.

93. T.D. Pham, C. C. To, H. Wang, X. Zhou, Analysis of major adverse cardiac events with entropy-based complexity, 2nd Int. Conf. Information Technologies in Biomedicine (ITiB’2010, 7-9 June 2010, Kamień Śląski, Poland) , E. Pietka and J. Kawa (Eds): Information Technologies in Biomedicine, AISC 69, pp. 261-272, Springer-Verlag Berlin Heidelberg, 2010.

94. T.D. Pham, Entropic analysis and synthesis of biosignal complexity, Proc. 3rd Int.  Joint Conf.  Biomedical Engineering Systems and Technologies (BIOSTEC 2010, 20-23 January 2010, Valencia, Spain) pp. 115-120, 2010.

95. T.D. Pham, X. Zhou, Ratio-hypothesis-based fuzzy fusion with application to classification of cellular morphologies, Proc. 3rd Int.  Joint Conf.  Biomedical Engineering Systems and Technologies (BIOSTEC 2010, 20-23 January 2010, Valencia, Spain) pp. 202-207, 2010.

96. J. Liu, T.D. Pham, Fuzzy hyper-clustering for pattern classification in microarray gene expression data analysis, Proc. 3rd Int.  Joint Conf.  Biomedical Engineering Systems and Technologies (BIOSTEC 2010, 20-23 January 2010, Valencia, Spain) pp. 415-418, 2010.

97. G. Zhang, X. Jia, T.D. Pham, D.I. Crane, Multistage spatial property based segmentation for quantification of fluorescence distribution in cells, AIP Proc. Int. Symp. Computational Models for Life Sciences 2009 (CMLS-09, Sofia, Bulgaria, 28 July 2009) pp. 3-12, 2010.

98. D. Yu, J.S. Jin, S. Luo, T.D. Pham, W. Lai, Description, recognition and analysis of biological images, AIP Proc. Int. Symp. Computational Models for Life Sciences 2009 (CMLS-09, Sofia, Bulgaria, 28 July 2009) pp. 23-44, 2010.

99. Q. Dai, L. Li, T. Pham, Novel probabilistic measures for DNA sequence comparison, AIP Proc. Int. Symp. Computational Models for Life Sciences 2009 (CMLS-09, Sofia, Bulgaria, 28 July 2009) pp. 45-56, 2010.

100. C. To, T.D. Pham, Binary classification using decision tree based genetic programming and its application to analysis of bio-mass data, AIP Proc. Int. Symp. Computational Models for Life Sciences 2009 (CMLS’09, Sofia, Bulgaria, 28 July 2009) pp. 103-109, 2010.

101. H.Z. El-fiqi, T.D. Pham, H.T. Hattori, D.I. Crane, Measuring complexity of mouse brain morphological changes using GeoEntropy, AIP Proc. Int. Symp. Computational Models for Life Sciences 2009 (CMLS’09, Sofia, Bulgaria, 28 July 2009) pp. 110-118, 2010.

102. T.F. Ng, T.D. Pham, X. Zhou, Justification of fuzzy declustering vector quantization modeling in classification of genotype-image phenotypes, AIP Proc. Int. Symp. Computational Models for Life Sciences 2009 (CMLS’09, Sofia, Bulgaria, 28 July 2009) pp. 119-130, 2010.

103. C. C. To, T.D. Pham, Understanding predictability of bio-signals using genetic algorithms and sample entropy, Biomedical Electronics and Biomedical Informatics (BEBI'09,  20-22 August 2009, Moscow, Russia) pp. 47-51, 2009.

104. T.D. Pham, Object recognition by permanence of ratios based fusion and Gaussian Bayes decision, Proc. 13th Int. Conf.  Knowledge-Based and Intelligent Information & Engineering Systems (28-30 September 2008, Santiago, Chile), J.D. Velasquez et al. (Eds.): KES 2009, Part I, LNAI 5711, pp. 156–161, 2009.

105. T.D. Pham, D. Fraser, M. Oyama-Higa, Psychophysiomatics: A new perspective in computational life science, Proc. 6th IEEE Int.  Symp.  Image and Signal Processing and Analysis (ISPA 2009, September 16-18, 2009, Salzburg, Austria), pp. 305-310, 2009.

106. Y. Itoh, M. Oyama-Higa, T.D. Pham, Influence of fractal dimensions on stimuli on searching reaction with focus on effects of objects included in stimuli images, Proc. 6th IEEE Int.  Symp.  Image and Signal Processing and Analysis (ISPA 2009, September 16-18, 2009, Salzburg, Austria) pp. 333-341, 2009.

107. C. To, T.D. Pham, Analysis of cardiac imaging data using decision tree based parallel genetic programming, Proc. 6th IEEE Int.  Symp.  Image and Signal Processing and Analysis (ISPA 2009, September 16-18, 2009, Salzburg, Austria) pp. 317-320, 2009.

108. T.D. Pham, U. Eisenblätter, J.  Golledge, B.T. Baune, K. Berger, Segmentation of medical images using geo-theoretic distance matrix in fuzzy clustering, Proc. IEEE Int. Conf. Image Processing (ICIP 2009, 7-11 November, Cairo, Egypt) pp. 3369-3372, 2009. 

109. T.D. Pham, Image and signal analysis in molecular biology and personalized medicine, Keynote lecture, Proc. IEEE Sixth International Multi-Conference on System, Signal and Devices (SSD'09, 23-26 March 2009, Djerba , Tunisia), pages: 1-9, DOI: 10.1109/SSD.2009.4956807.

110. D. Beck, X. Zhou, T. Pham, B. Sabatini, S.T.C. Wong, An image driven systems biology approach for neurodegenerative disease studies in the TSC-mTOR pathway, Proc. IEEE/NIH Life Science Systems and Applications Workshop 2009 (LISSA 2009, April 9-10, Bethesda, Maryland, USA) pp. 36-39, 2009.

111. T.D. Pham, U. Eisenblatter, A new spatial approach to image restoration, Proc. IEEE First Int. Workshop on Image Processing Theory, Tools and Applications (IPTA’08, November 23-26, 2008, Sousse, Tunisia) pp 443-450, 2008.

112. T.D. Pham, M. Brandl, D. Beck, A new approach for cancer classification using microarray gene expression data, Proc. IASTED Int. Symp. Computational Biology and Bioinformatics (CBB 2008, November 16-18, 2008, Orlando, Florida, USA) pp. 247-253, 2008.

113. D. Tran and T.D. Pham, Automated feature weighting-based cell phase classification, Proc. IASTED Int. Symp. Computational Biology and Bioinformatics (CBB 2008, November 16-18, 2008, Orlando, Florida, USA) pp. 274-277, 2008.

114. T.D. Pham, H. Wang, X. Zhou, D. Beck, M. Brandl, G. Hoehn, J. Azok, M-L. Brennan, S.L. Hazen, S.T.C. Wong, Classification of mass spectrometry based protein markers by kriging error matching, Proc. Int. Conf. Mass-Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry, and Food Industry (MDA 2008, 14 July 2008, Leipzig, Germany),  P. Perner and O. Salvetti (Eds.): MDA 2008, LNAI 5108, pp. 82–94, 2008.

115. V. Chandramohan, and T.D. Pham, Cancer classification using kernelized fuzzy c-means, Proc. 9th  Int. Conf. Fuzzy Systems (Sofia, Bulgaria, 2-4 May 2008), pp. 90-99, 2008.

116. T.D. Pham, M. Brandl, N.D. Nguyen, T.V. Nguyen, Fuzzy measure of multiple risk factors in the prediction of osteoporotic fractures, Proc. 9th Int. Conf. Fuzzy Systems (Sofia, Bulgaria, 2-4 May 2008), pp. 1711-177, 2008.

117. D. Yu, and T.D. Pham, Detection and analysis of cell nuclear phases, Proc. 12th Int. Conf.  Knowledge-Based and Intelligent Information & Engineering Systems (03-05 September 2008, Zagreb, Croatia), I. Lovrek, R.J. Howlett, and L.C. Jain (Eds.): KES 2008, Part I, LNAI 5177, pp. 401–408, 2008.

118. T.D. Pham, D. Beck, M. Brandl, and X. Zhou, Classification of proteomic signals by block kriging error matching, Proc. Int. Conf. Image and Signal Processing (ICISP 2008, Cherbourg-Octeville, France, July 1-3, 2008), A. Elmoataz et al. (Eds.), LNCS 5099, pp. 281–288, 2008.

119. T.D.  Pham, Fuzzy bio-image segmentation with spatial covariance, 12 Int. Conf. Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU’08, 22-27 June 2008, Málaga, Spain) L. Magdalena, M. Ojeda-Aciego, J.L. Verdegay (eds): Proceedings of IPMU'08, pp. 660-666, 2008.

120. D. Tran, T. Pham, X. Zhou, Subspace vector quantization and Markov modeling for cell phase classification, 2008 Int. Conf. Image Analysis and Recognition (ICIAR 2008,  25-27 June 2008, Póvoa de Varzim, Portugal), A. Campilho and M. Kamel (Eds.): ICIAR 2008, LNCS 5112, pp. 844–853, 2008.

121. T.D. Pham, J. Golledge, Geostatistically constrained fuzzy segmentation of abdominal aortic aneurysm CT images, Proc.  2008 IEEE Int. Conf. Fuzzy Systems (FUZZ-IEEE 2008, 1-6 June 2008, Hong Kong), pp. 1446-1451, 2008.

122. T.D. Pham, Cancer classification by minimizing fuzzy scattering effect, Proc.  2008 IEEE Int. Conf. Fuzzy Systems (FUZZ-IEEE 2008, 1-6 June 2008, Hong Kong), pp. 377-380, 2008.

123. D. Yu, T.D. Pham, X. Zhou, and S.T.C. Wong, Segmentation, recognition and tracing analysis for high-content cell-cycle screening, Proc. 2007 Int. Symp. Computational Models for Life Sciences (CMLS’07, 17 -19 December 2007, Gold Coast, QLD, Australia), AIP Conference Proceedings Volume 952, pp. 21-30, 2007.

124. D. Yu, T.D. Pham, H. Yan, W. Lai, and D.I. Crane, Segmentation and reconstruction of cultured neuron skeleton, Proc. 2007 Int. Symp. Computational Models for Life Sciences (CMLS’07, 17 -19 December 2007, Gold Coast, QLD, Australia) AIP Conference Proceedings Volume 952, pp. 66-75, 2007.

125. B. Zhang, T.D. Pham, Y. Zhang, Ovarian cancer identification from  mass spectra by kernel Fisher discriminant analysis, Proc. 2007 Int. Symp. Computational Models for Life Sciences (CMLS’07, 17 -19 December 2007, Gold Coast, QLD, Australia) AIP Conference Proceedings Volume 952, pp. 187-196, 2007.

126. B. Zhang, T. Pham, Y. Zhang, Bagging support vector machine for classification of SELDI-TOF mass spectra of ovarian cancer serum samples, (AI 2007, 2-6 December 2007, Gold Coast, QLD, Australia) LNCS 4830, 820-826, 2007.

127. T.D. Pham, Mass spectrometry based cancer classification using fuzzy fractal dimensions, 12th Iberoamerican Congress on Pattern Recognition (CIARP 2007, Viña del Mar / Valparaiso, Chile. November 13-16, 2007) CIARP 2007, LNCS 4756, pp. 614–623, 2007.

128. D. Yu, T.D. Pham, Analysis and recognition of touching cell images in cell-cycle screening based on morphological structures, 11th Int. Conf.  Knowledge-Based and Intelligent Information & Engineering Systems (KES 2007, 12-14 September 2007, Vietri sul Mare, Italy), LNCS 4692, pp. 439-446, 2007.

129. T.D. Pham, Fractal characteristics of mass spectrometry based cancer data, 3rd Int. Conf. Cellular and Molecular Biology, Biophysics and Bioengineering (BIO'07, 26-28 August 2007, Athens, Greece) pp. 30-35, 2007.

130. D. Yu, T.D. Pham, and X. Zhou, Tracing and recognition of cell phases, 3rd  Int. Conf. Cellular and Molecular Biology, Biophysics and Bioengineering (BIO'07, 26-28 August 2007, Athens, Greece) pp. 36-41, 2007.

131. T.D. Pham, Predictive modeling in proteomics-based disease detection, Proc. 29th Annual Int. Conf. IEEE Engineering in Medicine and Biology Society (IEEE-EMBC 2007, 23-26 August 2007, Lyon, France) pp. 3308-3311, 2007.

132. D. Yu, T.D. Pham, and D.I. Crane, A region analysis approach for segmenting neural-cell images, Proc. 29th Annual Int. Conf. IEEE Engineering in Medicine and Biology Society (IEEE-EMBC 2007, 23-26 August 2007, Lyon, France) pp. 5529-5532, 2007.

133. T.D. Pham, Geo-thresholding for segmentation of fluorescent microscopic cell images, Int. Conf. Mass-Data Analysis of Images and Signals in Medicine, Biotechnology, and Chemistry (MDA’2007, Leipzig, Germany, 17 July 2007), MDA 2007, LNAI 4826, pp. 15–26, 2007.

134. T.D. Pham, X. Zhou, A novel image feature for nuclear-phase classification in high content screening, Int. Conf. Mass-Data Analysis of Images and Signals in Medicine, Biotechnology, and Chemistry (MDA’2007, Leipzig, Germany, 17 July 2007), MDA 2007, LNAI 4826, pp. 84–93, 2007.

135. T.D. Pham, Double adaptive filtering of Gaussian noise degraded images, 15th Scandinavian Conference on Image Analysis (SCIA 2007, Aalborg, Denmark, June 10-14, 2007), LNCS 4522, pp. 848-857, 2007.

136. T.D. Pham, H. Wang, X. Zhou, D. Beck, M. Brandl, G. Hoehn, J. Azok, M.-L. Brennan, S.L. Hazen, K. Li, and S.T.C. Wong, Linear predictive coding and its decision logic for early prediction of major adverse cardiac events using mass spectrometry data,  Proc. AI06 Workshop on Intelligent Systems for Bioinformatics (04 December 2006, Hobart, Tasmania, Australia) pp. 61-66, 2006.

137. D. Yu, T.D. Pham, H. Yan, and D. Crane, Quantification of neural images using grey difference, Proc. AI06 Workshop on Intelligent Systems for Bioinformatics (04 December 2006, Hobart, Tasmania, Australia) pp. 73-80, 2006.

138. T.D. Pham, V. Chandramohan, X. Zhou, and S.T.C. Wong, Robust feature extraction and reduction of mass spectrometry data for cancer classification, Proc. IEEE ICDM Workshop on Data Mining in Bioinformatics (18-22 December 2006, Hong Kong) pp. 202-206, 2006 (Full paper).

139. T.D. Pham, Spatial linear predictive coding and its error matching for signal classification, Proc. 8th WSEAS Int. Conf.  Mathematical Methods and Computational Techniques in Electrical Engineering (Bucharest, Romania, October 16-18, 2006) pp. 276-281, 2006.

140. D. Yu, T.D. Pham, H. Yan, and D.I. Crane, Dynamic analysis and recognition of cell-cycle screening based on morphological structures, Proc. IEEE 6th Int. Conf.  Intelligent Systems Design and Applications (ISDA'06, 16-18 October 2006, Jinan, Shandong, China) vol. 2, pp. 1043-1048, 2006.

141. D.T. Tran, and T.D. Pham, Relaxation labeling for cell-phase identification, Proc. 2006 IEEE Int. Conf. Systems, Man and Cybernetics (IEEE-SMC 2006, 8-11 October 2006, Taipei, Taiwan), pp. 1275-1280, 2006.

142. T.D. Pham, and H. Yan, LPC-VQ based hidden Markov models for similarity searching in DNA sequences, Proc. 2006 IEEE Int. Conf. Systems, Man and Cybernetics (IEEE-SMC 2006, 8-11 October 2006, Taipei, Taiwan), pp. 1654-1659, 2006.

143. T.D. Pham, and D.T. Tran, Image classification by fusion for high-content cell-cycle screening, Proc. KES 2006 (9-11 October 2006, Bournemouth, UK), B. Gabrys, R.J. Howlett, and L.C. Jain (Eds.): KES 2006, Part I, LNAI 4251, pp. 524–531, 2006.

144. T.D. Pham, Similarity searching in DNA sequences by spectral distortion measures, Advances in Data Mining: Applications in Medicine, Web Mining, Marketing, Image and Signal Mining (6th Industrial Conference on Data Mining, ICDM 2006, Leipzig, Germany, July 14-15, 2006), Editor:  Petra Perner, LNCS 4065, 24 – 37, 2006.

145. T.D. Pham, Spectral analysis of protein sequences, Advances in Machine Learning and Cybernetics (ICMLC 2005, Guangzhou, China, August 18-21, 2005), revised selected papers, Editors: D.S. Yeung et al., LNCS 3930, 595–604, 2006.

146. T.D. Pham and D.T. Tran, Gaussian mixture and Markov models for cell-phase classification in microscopic imaging, Proc. IEEE Int. Conf. System of Systems Engineering (April 24-26, 2006, LA, USA) pp. 328-333, 2006.

147.  T.D. Pham, D.T. Tran, M. Brown, and R.L. Kennedy, Image segmentation of retinal vessels by fuzzy models, IEEE Proc. 2005 Int. Symp. Intelligent Signal Processing and Communication Systems (December 14-17, 2005, Hong Kong) pp. 541-544, 2005.

148. D. Tran, T.D. Pham, and X. Zhou, Cell phase identification using fuzzy Gaussian mixture models, IEEE Proc. 2005 Int. Symp. Intelligent Signal Processing and Communication Systems (December 14-17, 2005, Hong Kong) pp. 465-469, 2005.

149. D.T. Tran, and T.D. Pham, Cell phase classification using Markov and Gaussian mixture models, Proc. 2005 Asia-Pacific Workshop on Visual Information Processing (December 11-13, 2005, Hong Kong) pp. 48-52, 2005.

150. T.D. Pham, D. Tran, X. Zhou, S.T.C. Wong, An automated procedure for cell-phase imaging identification, Proc. AI-2005 Workshop on Learning Algorithms for Pattern Recognition (5-9 December 2005, Sydney, Australia) p. 22-29, 2005. 

151. T.D. Pham, and D.I. Crane, Segmentation of neuronal-cell images from stained fields and monomodal histograms, Proc. 27th Annual Int. Conf. IEEE Engineering in Medicine and Biology Society (September 1-4, 2005, Shanghai, China) paper 3.5.7-13, 2005.

152. T.D. Pham, An optimally weighted fuzzy k-NN algorithm (Int. Conf. Advances in Pattern Recognition 2005, August 22-25, 2005, Bath, UK), Editors: S. Singh et al., Lecture Notes in Computer Science, 3686 (2005) 239-247, 2005. 

153. T.D. Pham, and B.S. Shim, A cepstral distortion measure for protein comparison and identifica­tion, IEEE Proc. Int. Conf. Machine Learning and Cybernetics (August 18-21, 2005, Guangzhou, China) vol. 9, pp. 5609-5614, 2005. 

154. T.D. Pham, D.I. Crane, D. Tannock, and D. Beck, Kullback-Leibler dissimilarity of Markov models for phylogenetic tree reconstruction, IEEE Proc. 2004 Int. Symp. Intelligent Multimedia, Video & Speech Processing (Hong Kong, October 20-22, 2004), pp. 157-160, 2004. 

155. T.D. Pham, J. O’Connell, and D.I. Crane, Constrained codon optimization by dynamic program­ming, IEEE Proc. 2004 Int. Symp. Intelligent Multimedia, Video & Speech Processing (Hong Kong, October 20-22, 2004), pp. 153-156, 2004. 

156. T. Pham, J. O’Connell, and J. Zuegg, Euclidean distance measure of Markov mod­els for genome comparison without alignment, in: Currents in Computational Molecular Biology 2004, Eds. A. Gramada and P.E. Bourne, Inter. Conf.  Research in Computational Molecular Biology (RECOMB 2004) (San Diego, USA, 27-31 March 2004) pp. 348-349, 2004. 

157. T.D. Pham, Alignment-free sequence comparison with vector quantization and hidden Markov models, Proc. IEEE Computational Systems Bioinformatics Conference (CSB2003, 11-14 August 2003, Stanford, CA, USA), pp. 534-535, 2003. 

158. T.D. Pham, and D. Tran, VQ-based written language identification, Proc. IEEE-EURASIP Seventh Int. Symp. Signal Processing and its Applications (ISSPA 2003, 1-4 July 2003, Paris, France), Vol. 1, pp. 513-516 (ISBN 0-7803-7946-2), 2003. 

159. T.D. Pham, Vector quantization and fuzzy c-means clustering for written language classification, J-Marc Ogier and E. Trupin (Eds.), ICEIS Press, ISBN: 972-98816-3-4, Third Int. Workshop on Pattern Recognition in Information Systems (PRIS 2003), (April 22-23, 2003, Angers, France), pp. 104-112, 2003. 

160. T.D. Pham, Adaptive image restoration with spatial statistics, Proc. SPIE Conf. Image and Video Communications and Processing 2003 (Santa Clara, 20-23 January 2003), vol. 5022, pp. 1013-1021 (Published: May 2003). 

161. T.D. Pham, Variogram-based feature extraction for neural-network recognition of logos, Proc. SPIE Conf. Applications of Artificial Neural Networks in Image Processing VIII (Santa Clara, 20-23 January 2003), vol. 5015, pp. 22-29.

162. T.D. Pham, Applications of geostatistics and Markov models for logo recognition, Proc. SPIE Conf. Document Recognition and Retrieval X (Santa Clara, 20-23 January 2003), vol. 5010, pp. 20-27, 2003.

163. T.D. Pham, Recognition of trademarks with spatial statistics and neural learning, Proc. IEEE Int. Conf. Artificial Intelligence Systems 2002 (IEEE-AIS 2002, 5-10 September, Taganrog, Russia), pp. 205-210, 2002. 

164. T.D. Pham, A new approach for calculating implications of fuzzy rules, Proc. IEEE Int. Conf. Artificial Intelligence Systems 2002 (5-10 September, Taganrog, Russia), pp. 71-74, 2002. 

165. T.D. Pham, Combination of multiple classifiers using adaptive fuzzy integral, Proc. IEEE Int. Conf. Artificial Intelligence Systems 2002 (5-10 September, Taganrog, Russia), pp.  50-55, 2002. 

166. T.D. Pham, Clustering data with spatial continuity, Proc. IEEE Int. Conf. Fuzzy Systems (2-5 December 2001, Melbourne, Australia) volume 1, pp. 69-72, 2001. 

167. T. D. Pham, Image segmentation using probabilistic fuzzy c-means clustering, Proc. 2001 IEEE Int. Conf. Image Processing (ICIP 2001, 7-10 October 2001, Thessaloniki, Greece) volume 1, pp. 722-725, 2001. 

168. T.D. Pham, Mining data with hidden Markov models: Objective and subjective views, Int. Conf. Advances in Infrastructure for Electronic Business, Science, and Education on the Internet (SSGRR-2001, 6-12 August 2001, L’Aquila, Italy) refereed invited paper, in CD-ROM, 2001.

169. T. McConaghy, and T. Pham, A hierarchical fusion scheme for high-level design specifications, Proc. 4th Int. Conf. Information Fusion (Fusion 2001, 7-10 August 2001, Montreal, Canada) Volume 1, pp. TuA3: 9-13, 2001. 

170. J. Liang, T. McConaghy, A. Kochlan, T. Pham, and G. Hertz, Intelligent systems in analog circuit design: A survey, Proc. 5th World Multi-Conference on Systemics, Cybernetics and Informatics (SCI 2001, July 22-25, 2001, Orlando, Florida, USA) vol. IX, pp. 427-432, 2001. 

171. G. Hertz, and T. Pham, Visualization of high-dimensional tradeoff surfaces in analog design, Proc. 5th World Multi-Conference on Systemics, Cybernetics and Informatics (SCI 2001, July 22-25, 2001, Orlando, Florida, USA) vol. IX (Industrial Systems: Part I), pp. 410-414, 2001. 

172. G. Scott, D. Clark, and T. Pham, A genetic clustering algorithm guided by a descent algorithm, Proc. Congress on Evolutionary Computation 2001 (CEC2001, 27-30 May 2001, Seoul, Korea) vol. 2, pp. 734-740. 

173. T. Pham, M. Wagner, and D. Clark, Applications of genetic algorithms, geostatistics, and fuzzy c-means clustering to image segmentation, Proc. Congress on Evolutionary Computation 2001 (CEC2001, 27-30 May 2001, Seoul, Korea) vol. 2, pp. 741-746, 2001. 

174. T. Pham, Decision fusion for numeral recognition with fuzzy integral and neural network, Proc. Sixth International Conference on Control, Automation, Robotics and Computer Vision (ICARCV2000, Singapore, 5-8 December 2000) paper number in Conference CD-ROM #440, 2000. 

175. T.D. Pham, Fusion of Sobel, mean, and adaptive Wiener filters for restoring images degraded with Gaussian white noise, Proc. 2000 IEEE Int. Sym. on Intelligent Signal Processing and Communication Systems (ISPACS2000, Hawaii, USA, 5-8 November 2000) pp. 280-285, 2000. 

176. T.D. Pham and M. Wagner, Image restoration by fuzzy convex ordinary kriging, Proc. 2000 IEEE Int. Conf. on Image Processing (ICIP2000, Vancouver, Canada) pp. 1102-1105, 2000. 

177. T. Pham, Restoring greyscale images by fuzzy fusion, Proc. 4th World MultiConf. Systemics, Cybernetics and Informatics (SCI’2000) and 6th Int. Conf. Information Systems Analysis and Synthesis (ISAS’2000) (Orlando, USA, July 23-26, 2000), Vol. 3, pp. 596-601, 2000. 

178. T.D. Pham and M. Wagner, Information based speaker verification, Proc. 15th Int. Conf. on Pattern Recognition (ICPR2000, Barcelona, Spain) Volume 3, pp. 282-285, 2000. 

179. T.D. Pham, Image restoration by ordinary kriging with convexity, Proc. 15th Int. Conf. on Pattern Recognition (ICPR2000, Barcelona, Spain) Volume 3, pp. 334-337, 2000.

180. T. Pham, Genetic learning of multi-attribute interactions in speaker verification, Proc. Congress on Evolutionary Computation (CEC2000, San Diego, USA) vol. 1, pp. 379-383, 2000. 

181. M. Mohammadian, and T. Pham, A co-operative evolutionary-fuzzy logic control system with ap­plication to traffic signal control, Proc. 4th World MultiConf. Systemics, Cybernetics and Informatics (SCI’2000) and 6th Int. Conf. Information Systems Analysis and Synthesis (ISAS’2000) (Orlando, USA, July 23-26, 2000), Volume 3, pp. 591-595, 2000.

182. T. Pham and M. Wagner, Filtering noisy images using kriging, 5th Int. Sym. on Signal Processing and its Applications (ISSPA’99, Brisbane, Australia, 1999) pp. 427-430, 1999. 

183. D. Tran, M. Wagner, and T. Pham, Hard hidden Markov models for speech recognition, Proc. 4th World MultiConf. Systemics, Cybernetics and Informatics and 6th Int. Conf. Information Systems Analysis and Synthesis (Orlando, USA, July 23-26, 2000), Volume 3, pp. 614-619, 2000.

184. D. Tran, M. Wagner, and T. Pham, Hard Gaussian mixture models for speaker recognition, Proc. 4th World MultiConf. Systemics, Cybernetics and Informatics and 6th Int. Conf. Information Systems Analysis and Synthesis (Orlando, USA, July 23-26, 2000), Volume 3, pp. 608-613, 2000. 

185. T. Pham and M. Wagner, Abstraction and tolerance of imprecision in formal specification, Seventh Int. Conf. Fuzzy Theory and Technology (JCIS2000/FTT2000, Atlantic City, USA) Vol. 1, pp. 232-235, 2000. 

186. T. Pham, S. Shaw, D. Clark and M. Wagner, A neuro-fuzzy fusion of multiple classifiers, Third Int. Conf. Computer Vision, Pattern Recognition & Image Processing (JCIS2000/CVPRIP2000, Atlantic City, USA) Vol. 2, pp. 370-373, 2000.

187. T. Pham and M. Wagner, Fuzzy kriging filter for image restoration, Third Int. Conf. on Knowledge-Based Intelligent Information Engineering Systems (KES’99, Adelaide, Australia, 1999) pp. 333-336, 1999. 

188. D. Tran, T. Pham and M. Wagner, Speaker recognition using Gaussian mixture models and relaxation labeling, Proc. 3rd World MultiConf. Systemics, Cybernetics and Informatics and 5th Int. Conf. Information Systems Analysis and Synthesis (Orlando, USA 1999), Volume 6 (Image, Acoustic, Speech and Signal Processing) pp. 383-389, 1999. 

189. T. Pham and M. Wagner, Specification of fuzzy systems with fuzzy Z, Proc. 3rd World MultiConf. Systemics, Cybernetics and Informatics and 5th Int. Conf. Information Systems Analysis and Synthesis (Orlando, USA 1999), Volume 3, pp. 528-533, 1999. 

190. T.D. Pham, D. Tran and M. Wagner, Optimal fuzzy information fusion for speaker verifica­tion, Proc. Int. ICSC Congress on Computational Intelligence: Methods and Applications (CIMA’99/ISFL’99, New York, USA 1999) pp. 141-146, 1999. 

191. T.D. Pham, Towards flexible formal specifications with fuzzy information granulation, Proc. Int. Conf. Computational Intelligence for Modelling, Control and Automation (CIMCA’99, Vienna, Austria 1999), pp. 288-293, 1999. 

192. D. Tran, M. Wagner and T. Pham, Minimum classifier error and relaxation labelling for speaker recognition, Proc. Specom 98 (St Petersburg, Russia 1998) pp. 229-232, 1998. 

193. T.D. Pham and M. Wagner, Speaker identification using relaxation labeling, Proc. Fifth Int. Conf. Spoken Language Processing (Sydney, Australia 1998) Volume 2, pp. 209-212, 1998. 

194. T.D. Pham and M. Wagner, Fuzzy-integration based normalisation for speaker verification, Proc. Fifth Int. Conf. Spoken Language Processing (Sydney, Australia 1998) Volume 7, pp. 3273-3276, 1998. 

195. T.D. Pham, D. Tran and M. Wagner, Speaker verification using relaxation labeling, Proc. Workshop RLA2C (Speaker Recognition and its Commercial and Forensic Applications) (Avignon, France 1998) pp. 29-32, 1998. 

196. T.D. Pham and M. Wagner, Application of geostatistics to linear predictive coding of speech, Proc. CESA’98 (Computational Engineering in Systems Applications) IMACS Multiconference (Nabeul-Hammamet, Tunisia 1998) pp. 220-225, 1998. 

197. T. Pham and M. Wagner, Linear prediction analysis of speech based on geostatistics, Proc. Second Australasian Workshop on Signal Processing Applications (WoSPA)’97 (Brisbane, Australia 1997) pp. 47-50, 1997. 

198. A.R. Mirhosseini, H. Yan, C. Chen and T. Pham, Human face recognition: A minimal evidence approach, Proc. 6th Int. Conf. on Computer Vision (Bombay, India 1998) pp. 652-659, 1998. 

199. T.D. Pham and H. Yan, Fusion of handwritten numeral classifiers based on fuzzy and genetic algorithms, Proc. North America Fuzzy Information Processing Society (NAFIPS)’97 (New York, USA 1997) pp. 257-262, 1997. 

200. T.D. Pham and H. Yan, Combination of multi-classifier results using fuzzy integrals, Proc. Real World Computing (RWC)’97 (Tokyo, Japan 1997) pp. 260-267, 1997.

201. T.D. Pham and H. Yan, Color image segmentation – A fuzzy-integral mountain clustering ap­proach, Proc. Australian Pattern Recognition Society Image Segmentation Workshop’96 (Sydney, Australia 1996). 

202. T.D. Pham and H. Yan, Information fusion by fuzzy integral, Proc. 4th Australian and New Zealand Intelligent Information Systems Conference -ANZIIS’96 (Adelaide, Australia 1996) pp. 191-194, 1996.

203. S. Valliappan and T.D. Pham, Finite element discretization error analysis – Fuzzy logic approach, Proc. 5th Int. Conf. Education, Practice and Promotion of Computational  Methods in Eng. using Small Computers (Macao, 1995) pp. 45-53, 1995. 

204. T.D. Pham, S. Valliappan and M. Yazdchi, Modeling of fuzzy damping in dynamic finite element analysis, Proc. Int. Joint Conf. of Fourth IEEE Int. Conf. on Fuzzy Systems and Second Int. Fuzzy Engg. Symp (Yokohama, Japan 1995) pp.1971-1978, 1995. 

205. S. Valliappan and T.D. Pham, Computational mechanics and fuzzy logic – Marriage `ala mode, Keynote lecture, Abstr. Third World Congress on Computational Mechanics (Chiba, Japan 1994) pp.1500-1505, 1994. 

206. W.O. Yandell and T.D. Pham, A fuzzy control procedure for predicting fatigue crack initiation in asphaltic concrete pavement, Proc. IEEE World Congress on Computational Intelligence, Third IEEE Int. Conf. on Fuzzy Systems (Orlando, USA 1994) pp.1057-1062, 1994. 

207. T.D. Pham, Modeling of a fuzzy system in geotechnical engineering, Proc. IEEE World Congress on Computational Intelligence, Third IEEE Int. Conf. on Fuzzy Systems, (Orlando, USA 1994) pp.1861-1866, 1994. 

208. T.D. Pham, A new approach to measuring discretization error, Proc. 1st Australia-New Zealand Young Geotechnical Professionals Conference (Sydney, Australia 1994) pp.161-165, 1994. 

209. T.D. Pham and S. Valliappan, Finite element mesh generation using fuzzy logic, Invited lec­ture, Proc. 4th Int. Conf. on Education, Practice and Promotion of Computational Methods in Engineering using Small Computers (Dalian, China 1992) pp.1139-1144, 1992. 

210. S. Valliappan, T.D. Pham and V. Murti, Application of fuzzy sets in the finite element analysis of geotechnical problems, Proc. Computer Applications in Civil and Building Engineering (Kozo Systems Publishers, Tokyo, 1991) pp.111-118, 1991.