1. Book Chapters

  1. H Chang, J J Donatelli, P Enfedaque, G Freychet, M Haranczyk, A Hexemer, Z Hu, O Jain, H Krishnan, D Kumar, X Li, L Lin, M MacNeil, S Marchesini, X Mo, M Noack, K Pande, R Pandolfi, D Parkinson, D M Pelt, P Terciano, D A Shapiro, D Ushizima, C Yang, P H Zwart, J A Sethian, "Building Mathematics, Algorithms, and Software for Experimental Facilities", Handbook on Big Data and Machine Learning in the Physical Sciences, ( 2020) Pages: 189--240. [book chapter]

  2. Araujo, Carneiro, Silva, Medeiros, Ushizima, "Convolutional Neural Networks with Tensor Flow: theory and practice, p. 382-406. Brazilian Society of Computation Press 2017. [book chapter]

  3. Silva, Lopes, Araujo, Medeiros, Ushizima, "Computer Vision in python with libraries scikit-image & scikit-learn", p. 407-428. Brazilian Society of Computation Press 2017. [book chapter]

  4. Ushizima, D., "Detection and Classification of Cervical Cells" in The Practice of Reproducible Research: Case Studies and Lessons from the Data-Intensive Sciences, Kitzes, J., Turek, D., & Deniz, F. (Eds.), Oakland, CA: University of California Press 2017.[PDF] [book chapter]

  5. Ushizima, Geddes, Cormier-Michel, Bethel, Jacobsen, Prabhat, Ruebel, Weber, Hamann, Haggen, "Automated Detection and Analysis of Particle Beams in Laser-plasma Accelerator Simulations", InTech Press, 367-389, 2010.[bib][pdf] [book chapter]

2. Journals

  1. Badran, Parkinson, Ushizima, Marshall, Maillet, "Validation of Deep Learning Segmentation of CT Images of Fiber-Reinforced Composites" in Journal of Composites Sciences, Feb 2022 [pdf].

  2. Siqueira, Ushizima, van der Walt, "A reusable pipeline for large-scale fiber segmentation on unidirectional fiber beds using fully convolutional neural networks", Nature Scientific Data 2022 [arxiv] [pdf publisher]

  3. Sadre, Majumdar, Sundaram, Ushizima, "Validating deep learning inference during chest X-ray classification for COVID-19 screening", Nature Scientific Reports 2021 [pdf] [awarded].

  4. Rezende, Silva, Bernardo, Tobias, Oliveira, Machado, Costa, Medeiros, Ushizima, Carneiro, Bianchi, "Cric searchable image database as a public platform for conventional pap smear cytology data”, Nature Scientific Data 2021, 10.1038/s41597-021-00933-8 [pdf] [awarded].

  5. Noack, Zwart, Ushizima, Fukuto, Yager, Elbert, Murray, Stein, Doerk, Tsai, Li, Freychet, Zhernenkov, Holman, Lee, Chen, Rotenberg, Weber, Le Goc, Boehm, Steffens, Mutti, Sethian, "Gaussian Processes for Autonomous Data Acquisition at Large-Scale X-Ray and Neutron Scattering Facilities", Nature Reviews Physics, 2021 [pdf].

  6. Diniz, Rezende, Bianchi, Carneiro, Luz, Moreira, Ushizima, Medeiros, Souza, "A Deep Learning Ensemble Method to Assist Cytopathologists in Pap Test Image Classification", Journal of Imaging, 2021 [pdf]

  7. Xu, Tremsin, Li, Ushizima, Davy, Bouterf, Su, Marroccoli, Mauro, Osanna, Telesca, Monteiro, "Microstructure and Water Absorption of Ancient Concrete from Pompeii: An Integrated Synchrotron Microtomography and Neutron Radiography Characterization", Cement and Concrete Research, 2021 [link].

  8. Diniz, Victor, Bianchi, Silva, Carneiro, Ushizima, Medeiros, Souza, "A novel ensemble method for nuclei detection of overlapping cervical cells", Expert Systems With Applications, 2021 [link].

  9. Braga, Marques, Medeiros, Rocha, Bianchi, Carneiro, Ushizima, "Hierarchical median narrow band for level set segmentation of cervical cell nuclei", Measurements, 2021 [link].

  10. Viseshchitra, Ercius, Monteiro, Scott, Ushizima, Li, Xu, Wenk, "3D Nanotomography of Calcium Silicate Hydrates by Transmission Electron Microscopy", Journal of the American Ceramic Society 2020.

  11. Ushizima, Xu, Monteiro, "Materials Data Science for Microstructural Characterization of Archaeological Concrete", MRS Advances - special issue: Materials Data Science, 2020. [data] [code]

  12. Liu, Li, Bennett, Ganoe, Stauch, Head-Gordon, Hexemer, Ushizima, Head-Gordon, "A Multi-Resolution 3D-DenseNet for Chemical Shift Prediction in NMR Crystallography", The Journal of Physical Chemistry Letters, 2019.

  13. Silva, Araujo, Bianchi, Carneiro, Medeiros, Ushizima, "Radial Feature Descriptors for Cell Classification and Image Recommendation", Journal of Visual Communication and Image Representation, 2019.

  14. Liu, Melton, Venkatakrishnam, Pandolfi, Freychet, Kumar, Tang, Hexemer, Ushizima, "Convolutional Neural Networks for Grazing Incidence X-ray Scattering Patterns: Thin Film Structure Identification", Materials Research Society - Special Issue on Artificial Intelligence, pp.1-7, 2019.

  15. MacNeil, Ushizima, Panerai, Mansour, Barnard, Parkinson, "Interactive Volumetric Segmentation for Textile Microtomography Data using Wavelets and Non-local means", Journal of Statistical Analysis and Mining, Sep 2019.

  16. Araújo, Silva, Resende, Ushizima, Medeiros, Carneiro, Bianchi, "Deep Learning for Cell Image Segmentation and Ranking", Computerized Medical Imaging and Graphics, Mar 2019.

  17. Ke, Brewster, Yu, Yang, Ushizima, Sauter, "A Convolutional Neural Network-Based Screening Tool for X-ray Serial Crystallography", Journal of Synchrotron Radiation 2018.

  18. Araujo, Silva, Ushizima, Parkinson, Hexemer, Carneiro, Medeiros, "Reverse Image Search for Scientific Data within and beyond the Visible Spectrum", Expert Systems and Applications 2018 [bib] .

  19. Pandolfi, Allan, Arenholz, Barroso-Luque, Campbell, Caswell, Blair, Carlo, Fackler, Fournier, Freychet, Fukuto, Gursoy, Jiang, Krishnan, Kumar, Kline, Li, Liman, Marchesini, Mehta, N'Diaye, Parkinson, Parks, Pellouchoud, Perfiano, Ren, Sahoo, Strzalka, Sunday, Tassone, Ushizima, Venkatakrishnan, Yager, Zwart, Sethian, Hexemer, "Xi-cam: A versatile interface for data visualization and analysis", Journal of Synchrotron Radiation 2018.

  20. Araujo, Silva, Medeiros, Farias, Calaes, Bianchi, Ushizima, "Active contours for overlapping cervical cell segmentation", International Journal of Biomedical Engineering and Technology 2018.

  21. Williams, Ushizima, Zhu, Anders, Milliron, Helms, "Nearest-Neighbour Nanocrystal Bonding Dictates Framework Stability or Collapse in Colloidal Nanocrystal Frameworks", Chemical Communications, Royal Society of Chemistry, 2017.[PDF]

  22. Alegro, Theofilas, Nguy, Castruita, Seeley, Ushizima, Grinberg, Automating Cell Detection and Classification in Human Brain Fluorescent Microscopy Images Using Dictionary Learning and Sparse Coding, Journal of Neuroscience Methods, 2017.

  23. Perciano, Ushizima, Krishnan, Parkinson, Larson, Pelt, Bethel, Zok, Sethian, "Insight into 3D micro-CT data: exploring segmentation algorithms through performance metrics", Journal of Synchrotron Radiation, vol 24, issue 5, pg.1065-1077, 2017 [PDF]

  24. D. Ushizima, H. A. Bale, W. Bethel, P. Ercius, B. Helms, H. Krishnam, L. Grinberg, M. Haranczyk, M. A. A. Macdowell, K. Odziomek, D. Y. Parkinson, T. Perciano, R. Ritchie, and C. Yang. IDEAL: Images across Domains, Experiments, Algorithms and Learning, Journal of Minerals, Metals and Materials, 2016. JOM, 68(11), 2963-2972. doi:10.1007/s11837-016-2098-4 - Report Number: LBNL-1006616 [BibTeX] [PDF]

  25. Odziomek, Ushizima, Oberbek, Kurzydlowski, Puzyn, "Scanning electron microscopy image representativeness: morphological data on nanoparticles", Journal of Microscopy, 2016.[PDF]

  26. Santos, Bianchi, Ushizima, Pavinatto, Bianchi, "Ammonia gas sensor based on the frequency-dependent impedance characteristics of ultrathin polyaniline films", Sensors and Actuators A: Physical, 2016.[PDF]

  27. Lu, Carneiro, Bradley, Ushizima, Nosrati, Bianchi, Carneiro, Hamarneh, "Evaluation of Three Algorithms for the Segmentation of Overlapping Cervical Cells", IEEE Journal of Biomedical and Health Informatics, 99, pp. 2168-2194, 2016.[PDF]

  28. Venkatakrishnan, Mohan, Beattie, Correa, Dart, Deslippe, Hexemer, Krishnan, MacDowell, Marchesini, Patton, Perciano, Sethian, Stromsness, Tierney, Tull, Ushizima, Parkinson, "Making Advanced Scientific Algorithms and Big Scientific Data Management More Accessible", Electronic Imaging, 19, pp.1-7, 2016.[PDF]

  29. Wills, Michalak, Ercius, Rosenberg, Perciano, Ushizima, Runser, Helms. Block Copolymer Packing Limits and Interfacial Reconfigurability in the Assembly of Periodic Mesoporous Organosilicas. Advanced Functional Materials, 2015.[pdf]

  30. J. Donatelli, M. Haranczyk, A. Hexemer, H. Krishnan, X. Li, L. Lin, F. Maia, S. Marchesini, D. Parkinson, T. Perciano, D. Shapiro, D. Ushizima, C. Yang, J.A. Sethian. CAMERA: The Center for Advanced Mathematics for Energy Research Applications. Synchrotron Radiation News, 28:2, 2015.

  31. Paula Jr., I.C., Medeiros, F.N.S, Bezerra, F.N. and Ushizima, D.M., "Multiscale Corner Detection in Planar Shape", Journal of Mathematical Imaging and Vision, March 2013.[pdf]

  32. Ushizima, D.M., Morozov, D, Weber, G.H., Bianchi, A.G.C. and Bethel E.W., "Augmented topological descriptors of pore network", in: IEEE Trans. Comp Graph. and Vis. USA. LBNL-5964E [pdf]

  33. Carvalho, E.A., Ushizima,D.M., Medeiros,F.N.S., Martins,C.I.O., Marques,R.C.P., Oliveira,I.N.S., "SAR imagery segmentation by statistical region growing and hierarchical merging", Digital Signal Processing, Elsevier, Volume 20, Issue 5, Pages 1365-1378, Sept 2010.#20 Top Hottest Paper by ScienceDirect [bib]

  34. Leite,G.C., Ushizima,D.M., Medeiros,F.N.S., de Lima,G.G., "Wavelet Analysis for Wind Fields Estimation", Sensors, MDPI Press, ISSN 1424-8220, 10(6):5994-6016, 2010.[pdf][bib]

  35. Marques R C P, Medeiros F N S, Ushizima D M (2009), Target dectection on SAR images using level set methods, IEEE Transactions on Systems, Man and Cybernetics Part C (39):2:214-222. [pdf]

  36. Rubel,O. Geddes,C.G.R., Cormier-Michel,E., Wu,K., Prabhat, Weber,G.H., Ushizima,D.M., Messmer,P., Hagen,H., Hamann,B., and Bethel,E.W., "Automatic Beam Path Analysis of laser Wakefield Particle Acceleration Data", IOP Computational Science & Discovery, 2 015005 (38pp), Nov, 2009, LBNL-2734E.[pdf]

  37. Geddes, CGR, Cormier-Michel,E., Esarey,E.H., Schroeder,C.B., Vay,JL, Leemans,WP, Bruhwiler, Cary, JR., Cowan,B., Durant,M., Hamill, P., Messmer, P., Mullowney,P., Nieter,C., Paul,K., Shasharina, S., Veitzer,S., Weber,G., Rubel,O., Ushizima,DM, Prabhat, Bethel,E.W., Wu, K., "Large Fields for Smaller Facility Sources." SciDAC Review, Number 13, Summer 2009. LBNL-2299E [pdf]

  38. Ushizima Sabino D M, Costa LF, Calado RT, Zago MA (2004), A texture approach to leukocyte recognition, Real-Time Imaging 10(4):205-216.[pdf]

  39. Ushizima Sabino D M, Costa LF, Zago MA (2003), Automatic leukemia diagnostic, Acta Microscopica (12)1:1-6.[pdf]

3. Conferences (full paper):

  1. Ushizima, Araujo, Silva, Krishnan, Roberts, Hexemer, "Automated Sorting of X-ray Scattering Patterns with Convolutional Neural Networks", IPCV, Research Book Series: Transactions on Computational Science & Computational Intelligence,, 2021.

  2. Miramontes-Lizarraga, Piergies, Grinberg, Ushizima, "Accelerating Quantitative Microscopy with U-Net-based Cell Counting", IEEE 18th International Symposium on Biomedical Imaging (ISBI) Apr 2021.

  3. Ushizima, McCormick, Parkinson, "Accelerating Microstructural Analytics with Dask for Volumetric X-ray Imaging", PyHPC, 9th Workshop on Python for High-Performance and Scientific Computing, Supercomputing Nov 2020 [code].

  4. Parkinson, Krishnan, Ushizima, Henderson, Cholia, "Interactive Parallel Workflows for Synchrotron Tomography", XLOOP - 2nd Annual Workshop on Extreme-Scale Experiment-in-the-Loop-Computing, Supercomputing Nov 2020 [best presentation award].

  5. Araujo, Ushizima, Silva, "Fusion of color bands using genetic algorithm to segment melanoma", ISBI April 2020.

  6. Lima, Ushizima, Carvalho, Araujo, Lung CT screening with 3D convolutional neural network architecture, ISBI April 2020.

  7. Leemann, Amstutz, Ehrlichman, Hellert, Hexemer, Liu, Marcus, Melton, Nishimura, Penn, Sannibale, Shapiro, Sun, Ushizima, Venturini, "First Attempts at Applying Machine Learning to ALS Storage Ring Stabilization", 10th Int. Particle Accelerator Conference (IPAC2019), Melbourne, Australia 2019 [pdf]

  8. MacNeil, Morozov, Panerai, Parkinson, Barnard, Ushizima, "Distributed Global Digital Volume Correlation by Optimal Transport", Workshop on Large-Scale Experiment-in-the-Loop-Computing (XLOOP), Supercomputing 2019.

  9. Miramontes, Ushizima, "Evaluating fiber detection models using neural networks", ISVC Oct 2019.

  10. Lima, Vogado, Rabelo, Passarinho, Ushizima, "Entropy Projection Curved Gabor with Random Forest and SVM for Face Recognition", ISVC Oct 2019.

  11. White, Ushizima, Farhat, "Neural Networks Predict Fluid Dynamics Solutions from Tiny Datasets", arxiv 2019.

  12. Diniz, Calaes, Ushizima, Bianchi, Medeiros, Marcone, Carneiro, “An Iterated Local Search Algorithm for Cell Nuclei Detection from Pap Smear Images”, awarded best paper, ICEIS 2019 – 21st International Conference on Enterprise Information Systems, May 2019

  13. Ferreira, Ramalho, Bianchi, Carneiro, Ushizima, "Saliency-driven System with Deep Learning for Cell Image Classification", ISBI 2019 Venice, Italy, April 2019.

  14. Melo, Ushizima, Barachio, Coelho, "Gradient Boosting Decision Trees for Echo Images", IEEE World Congress on Computational Intelligence, International Joint Conference on Neural Networks (IJCNN) 2018.

  15. Oliveira, Moreira, Ushizima, Carneiro, Medeiros, Araujo, Silva, Bianchi, "A multi-objective approach for calibration and detection of cervical cells nuclei", IEEE Congress on Evolutionary Computation, 2017.

  16. Holdgraf, Rokem, Culich, Alegro, Deniz, Ushizima, “Portable Learning Environments for Hands-On Computational Instruction Using Container- and Cloud-Based Technology to Teach Data Science”, Practice & Experience in Advanced Research Computing Conference, PEARC’17.

  17. Parkinson, Pelt, Perciano, Ushizima, Krishnan, Barnard, MacDowell, Sethian, "Machine learning for micro-tomography", Developments in X-Ray Tomography, International Society for Optics and Photonics 2017.

  18. Ushizima, Hexemer, Parkinson, Yang, "Scaling Analytics for Scientific Images from Experimental Instruments", IEEE Applied Imagery Pattern Recognition, Oct 2016.(PDF)

  19. Araujo, Silva, Ushizima, Medeiros, "Searchable datasets in Python: images across domains, experiments, algorithms and learning", PyData San Francisco 2016.(PDF)

  20. Terciano, D.M. Ushizima, E.W. Bethel, Y.D. Mizrahi, D. Parkinson, J.A. Sethian. "Reduced-complexity image segmentation under parallel Markov random field formulation using graph partitioning", 2016 IEEE International Conference on Image Processing. LBNL-1005703. (BibTeX)

  21. Alegro, Amaro-Jr, Loring, Heinsen, Alho, Zollei, Ushizima, Grinberg, "Multimodal Whole Brain Registration: MRI and High Resolution Histology", IEEE Conference on Computer Vision and Pattern Recognition 2016. (PDF)

  22. Mascarenhas, Yang, Ushizima, "Quantization for Energy Efficient Convolutional Neural Networks", SC ’16 November 13 – 18, 2016, Salt Lake City, UT, USA. (PDF)

  23. Ushizima, Carneiro, Souza, Medeiros, "Investigating pill recognition methods for a new National Library of Medicine Image Dataset", Advances in Visual Computing: 11th Int. Symp, ISVC 2015, Las Vegas, NV, USA, Dec 14-16, 2015.

  24. Ushizima, D.M., Perciano, T., Krishnan, H., Loring, B., Bale, H., Parkinson, D., Sethian, J. "Structure recognition from high resolution images of ceramic composites", IEEE Int. Conf on Big Data, Washington, D.C., Oct 2014. LBNL-6900E. (PDF)

  25. Odziomek, K., Ushizima,D.M., Haranczyk,M., and Puzyn,T. "Toward quantitative structure activity relationship (QSAR) models for nanoparticles", American Chemical Society National Meeting - Scientific Excellence Award, August 2014. (PDF)

  26. Ushizima, D.M., Bianchi, A.G.C., Carneiro, "Segmentation of subcellular compartments combining superpixel representation with Voronoi diagrams", in: International Symposium on Biomedical Imaging 2014, Apr, Beijing, CH. 1st PLACE in Algorithm Challenge as part of the Overlapping Cervical Cytology Image Segmentation Challenge - ISBI'2014. LBNL-6892E. [pdf]

  27. Ushizima, D.M., Bianchi, A.G.C., deBianchi, C. and Bethel E.W., "Material science image analysis using quant-CT in ImageJ", in: ImageJ User and Developer Conference 2012, Oct, Luxembourg, LX. [pdf]

  28. Ushizima, D.M., Morozov, D, Weber, G.H., Bianchi, A.G.C. and Bethel E.W., "Augmented topological descriptors of pore network", in: VisWeek 2012, Oct, Seattle, WA, USA. [pdf]

  29. Bethel,E.W., Camp,D., Childs,H., Howison,M., Krishnan,H., Loring,B., Meyer,J., Prabhat, Ruebel,O., Ushizima,D.M., Weber,G.. "Towards Exascale: High Performance Visualization and Analytics" – Project Status Report. Technical Report LBNL-5767E. Lawrence Berkeley National Laboratory, Berkeley CA, USA, 94720. June, 2012. In DOE Exascale Research Conference, April 16–18, 2012, Portland OR, USA. (bibtex) (PDF)

  30. Ushizima, D.M., Ajo-Franklin, J., Macdowell, A., Morozov, D., Nico, P., Parkinson, Bethel E.W, Sethian J.A., "Statistical segmentation and porosity quantification of 3D x-ray microtomography", in SPIE Optics and Photonics: XXXIV Applications of Digital Image Processing, Vol.8135-1, pp.1-14, Aug 2011, San Diego, CA, USA. [pdf]

  31. Ushizima, D.M., Weber, G.H., Ajo-Franklin, J., Kim, Y., Macdowell, A., Morozov, D., Nico, P., Parkinson, D., Trebotich, D., Wan, J., and Bethel E.W., "Analysis and visualization for multiscale control of geologic CO2", in: Journal of Physics: Conference Series, Proceedings of SciDAC 2011, July 2011, Denver, CO, USA. LBNL publication number pending. [pdf]

  32. Leite,G., Medeiros,F., Ushizima,D.M., "Direction Estimation Using Texture Analysis", IEEE XVIII International Conference of Electrical, Electronic and Systems, Aug 8-13 2011.

  33. Uselton,A., Antypas,K., Ushizima,D.M., J.Sukharev, "File System Monitoring as a Window Into User I/O Requirements", CUG-2010, Edinburgh, UK, May 24-27th, 2010.

  34. Ushizima,D.M., Medeiros,F.N.S., Cuadros,J., Martins,C.I.O. "Vessel Network Detection Using Contour Evolution and Color Components", Proceedings of the 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Buenos Aires, Argentina. Sept 2010.[bib]

  35. Rubel, Ahearn, Bethel, Biggin, Childs, Cormier-Michel, DePace, Eisen, Fowlkes, Geddes, Hagen, Hamann, Huang, Keranen, Knowles, Luengo Hendriks, Malik, Meredith, Messmer, Prabhat, Ushizima, Weber and Wu, "Coupling visualization and data analysis for knowledge discovery from multi-dimensional scientific data", ICCS'2010, Procedia Computer Science Volume 1, Issue 1, May 2010, Pages 1751-1758. [pdf]

  36. Martins, CIO, Ushizima,DMU, Medeiros,FNS, Bezerra, FN, Marques,RCP, Mascarenhas,NDA, "Iterative Self-dual Reconstruction on Radar Image Recovery", Proc. of IEEE Workshop on Applications of Computer Vision, Snowbird, Utah, 37-42, 2009.

  37. E. W. Bethel, C. Johnson, S. Ahern, J. Bell, P.-T. Bremer, H. Childs, E. Cormier-Michel, M. Day, E. Deines, T. Fogal, C. Garth, C. G. R. Geddes, H. Hagen, B. Hamann, C. Hansen, J. Jacobsen, K. Joy, J. Kruger, J. Meredith, P. Messmer, G. Ostrouchov, V. Pascucci, K. Potter, Prabhat, D. Pugmire, O. Rubel. Sanderson, C. Silva, D. Ushizima, G. Weber, B. Whitlock, K. Wu. "Occam's Razor and Petascale Visual Data Analysis." In Journal of Physics Conference Series, Proceedings of SciDAC 2009. LBNL-2210E.

  38. Ushizima D M, Rubel O, Prabhat, Weber G, Bethel E W, Aragon C, Geddes C, Cormier-Michel E, Hamann B, Messmer P, Hagen H. "Automated Analysis for Detecting Beams in Laser Wakefield Simulations". 2008 Seventh International Conference on Machine Learning and Applications, Proceedings of IEEE ICMLA'08, 2008. LBNL-960E

  39. Ushizima D M, Calado R T, Rizzatti E G (2006), Leukocyte detection using nucleus contour propagation, Lecture Notes in Computer Science, LNCS 4091: 389-396.[pdf]

  40. Ushizima D M, Lourega L V, Freitas G D, d'Ornellas M C (2006), A Hybrid Image Segmentation Approach using Linear and Non-Linear Processing , International Symposium on Vision by Brains and Machines, Montevideo, Uruguay. CD-Rom.

  41. Ushizima D M, Lorena A C, Carvalho A C P L F (2005), Support vector machines applied to white blood cell recognition, V International Conference on Hybrid Intelligent Systems, pp. 379-384.

  42. Ushizima D M, Costa L da F, Zago M A (2005), Lymphocytic leukemia under machine vision, XVI Brazilian Symposium on Computer Graphics and Image Processing.

  43. Ushizima-Sabino D M, Costa L da F, Rizzatti E G, Zago M A, (2004), Toward leukocyte recognition using morphometry, texture and color, Proc. of IEEE International Symposium on Biomedical Imaging: From Nano To Macro (ISBI'04), Washington D.C., USA (awarded).

  44. Ushizima-Sabino D M, Costa L da F, Rizzatti E G, Zago M A, (2003), A texture approach to leukocyte recognition, Proc. Intern. Conference on Bioinformatics and Computational Biology, Ribeirao Preto, Brazil. CDRom.

  45. Ushizima-Sabino, D M., Costa, L.F., Calado, R.T., Zago, M.A. (2002), Chromatin texture characterization using multiscale fractal dimension, IEEE Proc. of 14th International Conference on Digital Signal Processing, Santorini, Greece, (2)1: 529-533.

4. Conferences/Meetings (short communications)

  1. Ushizima, "Advancing Lithium Metal Battery Design with Deep Learning", National Energy Storage Summit, Mar 2022 (finalist) [abstract].

  2. Ushizima, Quenum, Ying, Perlmutter, Su, Parkinson, Zenyuk, "Lithium Metal Battery Characterization using X-ray Imaging and Machine Learning", American Physical Society Mar 2022 [video].

  3. Parkinson, Noack, Krishnan, Enders, Ushizima, "Visualization for Remote Experiments At User Facilities", DOE ASCR Workshop on Visualization for Scientific Discovery, Decision-Making, & Communication 2022 [abstract].

  4. Ushizima, Singer, "Multiscale multimodal analysis allied to EcoPod", CSE 2021.

  5. Ushizima, Panod, Wenk, Monteiro, "Nanostructure Analysis of CSH TEM for Green Concrete Optimization", (in preparation) 2021 [code].

  6. Noack, Hexemer, Ushizima, "Gaussian Processes and Deep Learning for Experimental Data", American Physics Society 2021 [abstract].

  7. Sadre, Ushizima, "Computer Aided Diagnostic Tools for COVID-19 Detection via X-Ray Imaging", Urgent HPC: HPC for Urgent Decision Making, Supercomputing Nov 2020 [abstract].

  8. Miramontes S., Piergies A., Grinberg L., Ushizima D., Cell Counting with Quantitative Microscopy Based on U-Net, Frontiers in Machine Learning for the Physical Sciences, UC Irvine, Nov 2020 [abstract].

  9. Ushizima et al, "ACTS: Accelerating COVID-19 Testing with Screening", ADSA Annual Meeting Oct 2020.

  10. Ushizima, Xu, McCormick, Parkinson, Monteiro, "Machine Learning for Microstructural Characterization of Archeological Specimens from XRT", Session: Machine Learning Techniques in X-ray Analysis, 69th Denver X-ray Conference Aug 2020 [invited talk]

  11. Mladinov, Grinberg, Miramontes, Ushizima, "Cell detection from brain histology using artificial neural network", ISBI Apr 2020.

  12. Ushizima, Noack, Hexemer, "Machine Learning and Data Analytics: polymer films and beyond", Machine Learning and Data in Polymer Physics, American Physical Society, Mar 2020.

  13. Ushizima, "CAMERA, light, action: application to bioimaging", Workshop on Signal and Image Analysis for In Silico Heart Simulation, Sao Paulo, Oct 2019.

  14. Lizarra and Ushizima, “Efficient graph-based algorithm applied to cell detection”, UC Leads State competition - awarded best poster statewide in category Engineering & Computer Sciences, Feb 2019.

  15. Xu, Monteiro, Ushizima, “Unveiling the secrets of Roman Concrete with Computer Vision”, 2018 SSRL/LCLS Users' Meeting (poster).

  16. Alegro, Grinberg and Ushizima, “Deep learning for billion-pixel digital pathology analysis: application in mapping Tau protein in the human brain”, ML4Sci Sep 2018.

  17. Ke, Monteiro, Ushizima, “Revealing the secrets of Ancient Roman concrete structure through Machine Learning”, ML4Sci Sep 2018.

  18. Ferreira, Ushizima, “Saliency-driven system for image classification with deep learning”, ML4Sci Sep 2018.

  19. Ushizima and Lizarraga, “Spectral clustering for automated segmentation”, ML4Sci Sep 2018.

  20. Ushizima, “Scientific image recommendation using convnets”, ML4Sci Sep 2018.

  21. Ushizima, "Scientific Image Analysis with Convolutional Neural Networks, CoDA 2018, Santa Fe, NM, Mar 2018.

  22. MacNeil, Ushizima, Banard, Panerai, Parkinson, "Statistical Graphical Models and Deep Learning applied to Textile Composite Specimens", CoDA 2018, Santa Fe, NM, Mar 2018.

  23. Alegro, Chen, Castruita, Satrawada, Heinsen, Ushizima, Tsun, Grinberg, “Deep learning for billion-pixel digital pathology analysis: application in mapping Tau protein in the human brain”, Deep Learning in Biomedicine. UCSF, San Francisco CA, 2018.

  24. Perciano, Krishnan, Loring, MacNeil, Ushizima, "Mathematics in Pattern Recognition for Scientific Investigations", DOE ASCR Scientific Machine Learning Workshop, Washington DC, 2018.

  25. Ushizima, "Computer vision and deep learning for experimental observational images", Advanced Light Source User Meeting 2017, Lawrence Berkeley National Laboratory, Oct 2017. (PDF)

  26. Ushizima, Araujo, Silva, "Using convnets to find relevant cells", California Cognitive Science Conference, May 2017

  27. Ushizima, Grinberg, "Pathway toward diagnosing and monitoring prodromal Alzheimer's Disease using novel imaging biomarkers", California Initiative to Advance Precision Medicine Workshop 2016.

  28. Ushizima, D.M., "Scalability of Scientific Image Analysis", Informs Annual Meeting: Bringing Data and Decisions, San Francisco, CA, Nov 2014.

  29. Ushizima, D.M., Correa, J., Skinner, D., Bethel, E.W.,"Analysis and visualization of image-based experiments", Biomedical research: current challenges in computing conference (C3), IBM sponsored, Sep 2013.

  30. Ushizima, D.M., Bianchi, A.G.C., Krishnam, H., "Challenges and New Developments in Imaging with Large Data Sets", Joint Statistical Meeting (JSM2013), Montreal, Aug 2013 (oral presentation).

  31. Ushizima, D.M., Bianchi, A.G.C., Weihong, G., "Characterization of MRI brain scans associated to Alzheimer's disease through texture analysis", International Symposium on Biomedical Imaging: from Nano to Macro, Apr 2013.[pdf]

  32. Ushizima, D.M., Weber, G., Morozov, D., Bethel, W., Sethian, J.A., "Algorithms for Microstructure Description applied to Microtomography", Carbon Cycle 2.0 Symposium, LBNL, Fev. 10. 2012.[pdf]

  33. Uselton, A., Ushizima, D.M., "I/O Workload Analysis with Server-side Data Collection", SuperComputing 2011 (SC11), Seattle, WA, Nov. 13. 2011.

  34. C. Rycroft, D. M. Ushizima, R. Saye, K. Tanner, J. A. Sethian, "Coupling Physical Models to the Epithelial Cell Differentiation", Second Annual Physical Sciences - Oncology Centers Network Investigators' Meeting 2011, National Cancer Institute, San Diego, CA, Apr 2011.[pdf]

  35. D.M.Ushizima, "Statistical regions in porous media and 3D structure characterization", Bay Area Vision Meeting, Google, Apr 2011.

  36. C. Rycroft, D. M. Ushizima, R. Saye, C. M. Ghajar, J. A. Sethian, "Building a physical cell simulation and comparing with confocal microscopy", Bay Area Physical Sciences - Oncology Center (NCI) Meeting 2010, UCSF Medical Sciences, Sept 2010.

  37. D. Ushizima, K. Tanner, A. T. Lo, M. J. Bissel, J. Sethian, "Tracking cell dynamics from time-lapse LSM imagery, Physical Sciences - Oncology Centers Annual Site Visit, Berkeley, CA, Aug 2011.

  38. D. Ushizima, F. Medeiros, "Retinopathy diagnosis from ocular fundus image analysis", Modeling and Analysis of Biomedical Image, SIAM Conference on Imaging Science (IS10), Chicago, Il, April 12-14th, 2010.

  39. D. Ushizima and A.Uselton, K.Antypas and J. Sukharev "Minimizing I/O contention at NERSC using data analysis", Workshop on Algorithms for Modern Massive Data Sets (MMDS'10), Stanford, CA, June 15-18, 2010.[pdf]

  40. D. M. Ushizima and J. Cuadros, "Ocular fundus and retinopathy characterization", Bay Area Vision Meeting, Feb 5th, Berkeley, CA 2010.

  41. Martins C I O, Veras R M S, Ramalho G L B, Medeiros F N S, Ushizima D M, "Automatic Microaneurysm Detection and Characterization Through Digital Color Fundus Images". Brazilian Artificial Intelligence Community Conference, Tenth Brazilian Symposium on Neural Networks, SBRN'2008.

  42. Marques R C P, Medeiros F N S, Ushizima D M (2006), Tracking Targets in Simulated Speckled Images, XVII Brazilian Symposium on Computer Graphics and Image Processing. CD-Rom.

  43. Ushizima D M (2006), Ampliando o hemograma com microscopia quantitativa, III Workshop Tecnologico da Cientistas Associados (WTCA), Sao Carlos, Brazil. CD-Rom.

  44. Ushizima D M, Rosatelli M C (2007), Medical Diagnostic System driven by Pattern Recognition and Collaborative Learning, XIX US National Congress on Computational Mechanics (USNCCM9).

  45. Lourega L V, Ushizima D M, Freitas G D, d'Ornellas M C (2006), MeSegHi: Metodo de Segmentacao por Processamento Linear e Nao-Linear de Imagens, II Workshop em Visao Computacional, Sao Carlos, Brazil. CD-Rom.

  46. Ushizima D M, Senger H, d'ornellas M C, Medeiros F N S (2005), Quantitative microscopy applied to cytology and material microstructure, XVI Brazilian Symposium on Computer Graphics and Image Processing. CD-Rom.

  47. Ushizima D M, Rosatelli M (2005), E-learning in medical diagnosis, XVI Brazilian Symposium on Computer Graphics and Image Processing. CD-Rom.

  48. Ushizima-Sabino D M, Consularo L A, Costa L da F, Manjunath B S, (2004) , Fast image segmentation: quantitative evaluation and image applications, XV Brazilian Symposium on Computer Graphics and Image Processing. CD-Rom.

  49. Ushizima-Sabino D M, Costa L da F, (2003), Feature selection methods applied to multiscale curvature, XIV Brazilian Symposium on Computer Graphics and Image Processing, SIBGRAPI'03. CD-Rom.

  50. Ushizima-Sabino D M, Mendes T, Costa L da F, (2003), Clusterizacao de dados de leucocitos usando o modelo superparamagnetico, Escola de Computacao de Alto Desempenho para Sistemas Complexos, Sao Carlos, Brazil. CD-Rom.

  51. Ushizima-Sabino, D M, Costa, L da F, (2002), Diagnostico de leucemia por computador, I Workshop Regional de Engenharia Biomedica, EESC, Sao Carlos, Brazil. CD-Rom.

  52. Ushizima-Sabino, D M, Costa, L.F., Martins S.R.L., Zago M.A. (2001), Diagnostico automatico de leucemia, V Workshop de Pos Graduacao em Fisica, IFSC, Sao Carlos, Brazil. CD-Rom.

  53. Ushizima-Sabino, D M, Costa, L.F., Martins S.R.L., Zago M.A. (2001), Automatic leukemia diagnostic in XVIII CSBMM 2001, Aguas de Sao Pedro, SP, Brazil. CD-Rom.

  54. Ushizima-Sabino, D M, Costa, L.F. (2001), Diferenciacao de leucocitos por computador in Hemato 2001, Fortaleza, CE, Brazil.

  55. Ushizima D M (2004), Diagnostico de leucemia linfoide auxiliado por computador, Instituto de Fisica de Sao Carlos, University of Sao Paulo, Brazil; Ph.D. thesis.

5. Invited talks (selected):

  • Ushizima, Noack, Hexemer, "Gaussian Processes and Deep Learning for Experimental Data", Machine Learning and Data in Polymer Physics II, American Physical Society, Mar 2021[link].

  • Ushizima, "Machine Vision for X-ray Imaging, Intelligent Search & AutoML", Women in Data Science (WiDS) Brazil, Oct 2020 [pdf/code].

  • Ushizima, "Machine Vision for X-ray Imaging, Intelligent Search & AutoML", AI/ML for ALS Research Innovation Forum, Aug 2020 [pdf/code].

  • Ushizima, "Machine vision at Berkeley Lab", SAGE-S Program, Aug 2020 [pdf/code]

  • Ushizima, "Computer vision for imaging science", STROBE Lecture, June 2020 [pdf/code].

  • Ushizima, "Machine Vision for X-ray Imaging, Intelligent Search & AutoML", Women in Data Science (WiDS) Berkeley, March 2020 [video].

  • Ushizima and Lizarraga, “Mentor-mentee relationship”, SULI Seminar, June 13th 2019.

  • Ushizima, “Image across Domains, Experiments, Algorithms and Learning”, Pelosi Staff Visit to LBNL, May 2019.

  • Ushizima, “Thin Film Structure Identification through Convolutional Neural Networks applied to Scattering Patterns”, WK1: Driving Scientific Discovery with Artificial Intelligence, Advanced Data Analysis, and Data Management in the APS-U Era” at the 2019 Advanced Photon Source/Center for Nanoscale Materials/Electron Microscopy Center Users Meeting, May 6-9, 2019.

  • Ushizima, “Machine Learning and computer vision for images across domains”, University of Basilicata, Potenza, Italy (university distinguished seminar), April 2019;

  • Ushizima, “Machine Learning and computer vision for images across domains”, Dagstuhl Scholls Seminars, April 2019;

  • Ushizima, “Machine Learning for Materials Science”, CS Review, Feb 2019.

  • Ushizima, “Searching for the faces of human cells”, Precision Medicine World Conference, Precision Imaging Panel - Santa Clara, Jan 2019.

  • Ushizima, “Revealing the microstructures of Ancient Roman Concrete: X-ray micro-CT and Machine Learning”, ALS Tomography workshop, Nov 2018;

  • Ushizima, “Machine Learning and computer vision for images across domains”, San Jose State University (university distinguished seminar), Oct 2018;

  • Ushizima, “Machine Learning for Scattering Analysis”, SSRL/LCLS ML Workshop, Sep 2018.

  • Ushizima, "Machine Learning and science applications", TechWomen Enrichment Webinar, US. Dept of State I.E.E. Aug 2018.

  • "Search for Scientific Data: characterization, retrieval and ranking for multi-modal imaging"

  • "Machine Learning and science applications"

    • TechWomen Enrichment Webinar, US. Dept of State I.E.E. Aug 2018.

  • "Scientific Image Analysis with Convolutional Neural Networks"

  • "High Throughput Reverse Image Search with pyCBIR: Quantification, Search, Retrieval and Ranking for Multi-modal Imaging”,

    • Workshop in Multi-dimensional and Multi-modal X-ray Imaging and Analysis, Making and Measuring in 4-Dimensions, NSLS-II and CFN User’s Meeting, Brookhaven National Laboratory 2017.

    • Host/Chair: Karen Chen, BNL, Apr 2017.

  • How images shape your life, and shapes from images

    • LBNL Workforce Development and Education Seminar, Berkeley, CA

    • Host/Chair: Laleh Esmaili Cote, Undergraduate Internship Coordinator, Berkeley, Fev 2014.

  • Energy technologies meets computing and data analysis

    • EETD Seminar Series, LBL, Berkeley, CA

    • Host/Chair: Scott Young, Research Scientist, Environmental Energy Tech, EETD, Jan 2014. [PDF]

  • Multimodal and Multiresolution Analysis and Visualization of Experimental Data

    • Informs: Data Mining in Medical Decision Making and Bioinformatics Applications, Minneapolis, Minnesota

    • Host/Chair: Kamran Paynabar,Georgia Institute of Technology, Atlanta, 2013.

  • Data analysis and visualization for the Brain Initiative

  • Aquisicao de imagens digitais em experimentos cientificos: desafios, resultados e perspectivas

    • Seminar at Universidade Federal de Ouro Preto

    • Host: Andrea Bianchi, UFOP, 2013.

  • Image analysis of experimental data

  • Analysis and Visualization of High-throughput Experiments

  • High School Outreach

    • Host: LBNL, 2013.

    • Approaches to retinal image analysis

  • VI Annual Berkeley Conference on Translational Research "Improving Access to Eye Care through Translational Research"

    • Host: Jorge Cuadros, 2012.

  • Carbon dioxide, traps and x-ray vision

  • Computed tomography analysis in multiscale control of geologic CO2

    • Free University of Berlin, Germany: Institute of Computer Science and Konrad Zuse Institute of Information Technology, Berlin

    • Host: Ingrid Holtz, 2011

  • Quant-CT: segmenting and quantifying computed tomography

    • 2011 Advanced Light Source User Meeting, "Analyzing Tomographic Data Sets: From the Micro- to the Nano-Scale", Berkeley, CA

    • Host: ALS Tomography Workshop

  • From breast cancer to carbon sequestration: image analysis on science applications, 2011

    • Fraunhofer HHI, Einsteinufer 37, 10587 Berlin, Germany

    • Host: Jurgen Rurainsk

  • Material and medical image segmentation using SRM and fast marching

    • Humboldt University, Math Department, Berlin, Germany

    • Imaging science at Lawrence Berkeley National Laboratory

  • Panel: Opportunities for Research Outside Academia

    • Empowering Leadership Alliance National Meeting: April 2-3, 2011.

  • Enabling a next generation of science breakthroughs via computer science, 2010.

    • Grace Hopper Conference, Atlanta, GA;

  • Automated retinopathy screening using ocular fundus images, 2010.

    • UC Berkeley, Berkeley, CA;

  • Computer vision and real world applications, 2007.

    • Smith-Kettlewell Eye Research Institute, San Francisco, CA, USA;

    • Host: James Coughlan;

  • Data Analysis Using the R for Statistical Computing , 2009.

    • Tec-X, Boulder, CO, USA;

    • Host: NERSC User Group (NUG);

  • Computer vision applications: leukemia diagnosis, radar images and coffee classification automation, 2007.

    • Lawrence Berkeley National Laboratory;

    • Host: Edward Wes Bethel;

  • Computer-aided lymphoproliferative leukemia diagnosis, 2004.

    • Lawrence Berkeley National Laboratory, DOE, Berkeley, USA;

    • Host: J. A. Sethian;

  • Computer-aided lymphoproliferative leukemia diagnosis, 2004.

    • Electrical and Computer Engineering Department, University of California, Santa Barbara, USA;

    • Host: B.S. Manjunath;

  • Computer Aided Leukemia Diagnosis, 2002.

    • Intelligent Systems & Artificial Vision Lab, University of Salerno, Italy;

    • Host: Mario Vento.

5. In the media (selected)

6. Datasets

More info at ResearchGate