Publications

Books

"Chapter 11: Tensor methods for low-level vision"T. Yokota, C.F. Caiafa, and Q. ZhaoIn Tensors for Data Processing, Elsevier, 2021.

Journals


[19] "Electric Field Regression and Error Variance Estimation for Transcranial Magnetic Stimulation using Deep Neural Networks"T. Maki, T. Yokota, A. Hirata, and H. Hontani.Advanced Biomedical Engineering, Vol.12, pp. 225-235, 2023.
[18] "A New Model for Tensor Completion: Smooth Convolutional Tensor Factorization"H. Takayama and T. Yokota.IEEE Access, vol.11, pp. 67526-67539, 2023.
[17] Bayesian tensor completion and decomposition with automatic CP rank determination using MGP shrinkage prior"H. Takayama, Q. Zhao, H. Hontani, and T. Yokota.SN Computer Science, vol.3, no. 225, 2022.
[16] "Subtype Classification of Malignant Lymphoma Using Immunohistochemical Staining Pattern"N. Hashimoto, K. Ko, T. Yokota, K. Kohno, M. Nakaguro, S. Nakamura, I. Takeuchi, and H. Hontani.International Journal of Computer Assisted Radiology and Surgery, 2022.
[15] "Manifold Modeling in Embedded Space: An Interpretable Alternative to Deep Image Prior"T. Yokota, H. Hontani, Q. Zhao, and A. Cichocki.IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 3, pp. 1022-1036, 2022.
[14] "Matrix and Tensor Completion in Multiway Delay Embedded Space Using Tensor Train, with Application to Signal Reconstruction"F. Sedighin, A. Cichocki, T. Yokota, and Q. Shi.IEEE Signal Processing Letters, vol. 27, pp. 810-814, 2020.
[13] “Robust 3D image reconstruction of pancreatic cancer tumors from histopathological images with different stains and its quantitative performance evaluation”M. Kugler, Y. Goto, Y. Tamura, N. Kawamura, H. Kobayashi, T. Yokota, C. Iwamoto, K. Ouchida, M. Hashizume, A. Shimizu, and H. Hontani.International Journal of Computer Assisted Radiology and Surgery, vol. 14, issue 12, pp. 2047-2055, 2019.
[12] “Real Time Estimation of Electric Fields Induced by Transcranial Magnetic Stimulation with Deep Neural Networks”T. Yokota, T. Maki, T. Nagata, T. Murakami, Y. Ugawa, I. Laakso, A. Hirata, and H. Hontani.Brain Stimulation, vol. 12, issue 6, pp. 1500-1507, 2019.
[11] “Simultaneous Tensor Completion and Denoising by Noise Inequality Constrained Convex Optimization”T. Yokota, and H. Hontani.IEEE Access, vol. 7, no. 1, 15669-15682, 2019.
[10] “Super-Resolution of Magnetic Resonance Images via Convex Optimization with Local and Global Prior Regularization and Spectrum Fitting”N. Kawamura, T. Yokota, and H. HontaniInternational Journal of Biomedical Imaging, vol. 2018, Article ID 9262847, 17 pages, 2018.
[9] “Semi-Automated Biomarker Discovery from Pharmacodynamic Effects on EEG in ADHD Rodent Models”T. Yokota, Z.R. Struzik, P. Jurica, M. Horiuchi, S. Hiroyama, J. Li, Y. Tanaka, K. Ogawa, K. Nishitomi, and M. HasegawaScientific Reports, vol. 8, no. 5202, 2018.
[8] “Parametric PET Image Reconstruction via Regional Spatial Bases and Pharmacokinetic Time Activity Model”N. Kawamura, T. Yokota, H. Hontani, M. Sakata, and Y. KimuraEntropy, vol. 19, no. 11, 629, 2017.
[7] “Robust Multilinear Tensor Rank Estimation Using Higher Order Singular Value Decomposition and Information Criteria”T. Yokota, N. Lee, and A. CichockiIEEE Transactions on Signal Processing, vol. 65, issue 5, pp. 1196-1206, 2017.
[6] “Smooth PARAFAC Decomposition for Tensor Completion”T. Yokota, Q. Zhao, and A. CichockiIEEE Transactions on Signal Processing, vol. 64, issue 20, pp. 5423-5436, 2016.(IEEE Signal Processing Society Japan Young Author Best Paper Award)
[5] “EEG Correlates of Voice and Face Emotional Judgments in the Human Brain”K. Hiyoshi-Taniguchi, M. Kawasaki, T. Yokota. H. Bakardjian, H. Fukuyama, A. Cichocki, and F.B. VialatteCognitive Computation, vol. 7, no.1, pp. 11-19, 2015.
[4] “Smooth Nonnegative Matrix and Tensor Factorizations for Robust Multi-way Data Analysis”T. Yokota, R. Zdunek, A. Cichocki, and Y. YamashitaSignal Processing, vol. 113, no. 0, pp. 234-249, 2015.
[3] “Multiple kernel learning for quadratically constrained MAP classification”Y. Washizawa, T. Yokota, and Y. YamashitaIEICE Transactions on Information and Systems, vol. 97, no. 5, pp. 1340-1344, 2014.
[2] “A Quadratically Constrained Maximum A Posteriori Classifier Using the Mixture of Gaussians Models as a Weight Function”T. Yokota, and Y. YamashitaIEEE Transactions on Neural Networks and Learning Systems, vol. 24, issue 7, pp. 1127-1140, July 2013.
[1] “The interpolated local model fitting method for accurate and fast single-shot surface profiling”T. Yokota, M. Sugiyama, H. Ogawa, K. Kitagawa, and K. SuzukiApplied Optics, vol. 48, no. 18, pp. 3497-3508, 2009.

Conferences


[40] "Modification of DDIM Encoding for Generating Counterfactual Pathology Images of Malignant Lymphoma"Ryoichi Koga, Mauricio Kugler, Tatsuya Yokota, Kouichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi, Noriaki Hashimoto, Ichiro Takeuchi, Hidekata HontaniVISAPP, 2024.
[39] "Efficient implementation and acceleration of DIP-NMF-MM algorithm for high-precision 4D PET image reconstruction"Yoshinao Yuasa, Kaito Matsumura, Tatsuya Yokota, Satoshi Ohshima, Hidekata Hontani, Toru Nagai, Yuichi Kimura, Muneyuki Sakata, Takahiro KatagiriHPC Asia, 2024.
[38] "Stain Conversion from H&E to BRAF by using StyleGAN"
Toyohiro Maki, Mauricio Kugler, Tatsuya Yokota, Satomi hatta, Kunihiro Inai, and Hidekata Hontani
 IFMIA, 2023.

[37] "Anomaly Detection for Chest CT Images using Normalizing Flow"
Hiroki Tobise, Mauricio Kugler, Tatsuya Yokota, Masahiro Hashimoto, Yoshito Otake, Toshiaki Akashi, Akinobu Shimizu and Hidekata Hontani
IFMIA, 2023.

[36] "Graph neural network for identification of malignant lymphoma subtypes and class activation visualization of cell tissue anomality"Tanaka H., Hashimoto N., Yokota T., Kugler M., Ohshima K., Miyoshi H., Nagaishi M., Takeuchi I., Hontani H.
IFMIA, 2023.
[35] "Construction of Classifier for malignant lymphoma nuclei using label propagation"
Koide S., Kugler M., Yokota T., Ohshima K., Miyoshi H., Nagaishi M., Hashimoto N., Takeuchi I., Hontani H.
IFMIA, 2023.

[34] "Generation of Counterfactual Images to Construct Criteria for Quantitatively Evaluating Subtypes in Malignant Lymphoma"Ryoichi Koga, Mauricio Kugler, Tatsuya Yokota, Kouichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi, Noriaki Hashimoto, Ichiro Takeuchi, Hidekata HontaniIFMIA, 2023.
[33] "Consistent MDT-Tucker: A Hankel Structure Constrained Tucker Decomposition in Delay Embedded Space"R. Yamamoto, H. Hontani, A. Imakura, and T. Yokota
APSIPA-ASC, 2022.
[32] "Fast Signal Completion Algorithm With Cyclic Convolutional Smoothing"H. Takayama, and T. YokotaAPSIPA-ASC, 2022.

[31] "Fast Algorithm for Low-rank Tensor Completion in Delay-embedded Space"R. Yamamoto, H. Hontani, A. Imakura, and T. YokotaCVPR, 2022.(poster, acceptance rate=25.3%)
[30] "Detection of DLBCL regions in H&E stained whole slide pathology images using Bayesian U-Net"Ryoichi Koga and Noriaki Hashimoto and Tatsuya Yokota and Masato Nakaguro and Kei Kohno and Shigeo Nakamura and Ichiro Takeuchi and Hidekata HontaniIFMIA, 2021.
[29] "Stain transfer for automatic annotation of malignant lymphoma regions in H&E stained whole slide histopathology images"Ryoichi Koga and Noriaki Hashimoto and Tatsuya Yokota and Masato Nakaguro and Kei Kohno and Shigeo Nakamura and Ichiro Takeuchi and Hidekata HontanIFMIA, 2021.
[28] "Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting"Q. SHI, J. YIN, J. CAI, A. Cichocki, T. Yokota, L. CHEN, M. Yuan, and J. ZengAAAI, 2020.(poster, acceptance rate=20.6%)
[27] "Construction of a Multi-modal Model of Pancreatic Tumors by Integration of MRI and Pathological Images using Conditional Cycle alpha-GAN"T. Shimomura, M. Kugler, T. Yokota, C. Iwamoto, K. Ohuchida, M. Hashizume, and H. HontaniICCV Workshop for Multi-Discipline Approach for Learning Concepts (MDALC), 2019(poster, extended abstract)
[26] “Dynamic PET Image Reconstruction Using Nonnegative Matrix Factorization Incorporated with Deep Image Prior”T. Yokota, K. Kawai, M. Sakata, Y. Kimura, and H. HontaniICCV, 2019.(oral, acceptance rate=4.3%)
[25] “Registration between histopathological images with different stains and an MRI Image of Pancreatic Cancer Tumor”H. Hontani, Y. Goto, Y. Tamura, T. Shimomura, N. Kawamura, H. Kobayashi, M. Kugler, T. Yokota, C. Iwamoto, K. Ohuchida, M. Hashizume, T. Katagiri, T. Sei, and A. shimizuIWAIT-IFMIA, 2019.
[24] “PARTIAL RIGID DIFFEOMORPHISM FOR MEASURING TEMPORAL CHANGE OF PANCREATIC CANCER TUMOR”Y. Tamura, T. Yokota, M. Kugler, V. Triquet, T. Sei, C. Iwamoto, K. Ohuchida, M. Hashizume, and H. HontaniIWAIT-IFMIA, 2019.
[23] “CONSTRUCTION OF MULTIMODAL 3D MODEL OF PANCREATIC CANCER TUMOR”Y. Goto, H. Hontani, T. Yokota, M. Kugler, C. Iwamoto, K. Ohuchida, and M. HashizumeIWAIT-IFMIA, 2019.
[22] “Tensor Completion with Shift-invariant Cosine Bases”T. Yokota, and H. HontaniAPSIPA-ASC, 2018.
[21] “Simultaneous PET Image reconstruction and Feature Extraction Method Using Non-negative, Smooth, and Sparse Matrix Factorization”K. Kawai, H. Hontani, T. Yokota, M. Sakata, and Y. KimuraAPSIPA-ASC, 2018.
[20] “Construction of a Generative Model of H&E Stained Pathology Images of Pancreas Tumors Conditioned by a Voxel Value of MRI Image”T. Shimomura, K. Mauricio, T. Yokota, C. Iwamoto, K. Ohuchia, M. Hashizume,and H. HontaniMICCAI COMPAY 2018 Workshop, 2018.
[19] “Accurate 3D reconstruction of a whole pancreatic cancer tumor from pathology images with different stains”M. Kugler, Y. Goto, N. Kawamura, H. Kobayashi, T. Yokota, C. Iwamoto, K. Ohuchida, M Hashizume, and H. HontaniMICCAI COMPAY 2018 Workshop, 2018.
[18] “Missing Slice Recovery for Tensors Using a Low-rank Model in Embedded Space”T. Yokota, B. Erem, S. Guler, S. Warfield, and H. HontaniCVPR, 2018.(poster, acceptance rate = 29.1%)
[17] “Landmark-based reconstruction of 3D smooth structures from serial histological sections”N. Kawamura, H. Kobayashi, T. Yokota, H, Hontani, C. Iwamoto, K. Ohuchida, and M. Hashizume.SPIE Medical Imaging, 2018. (Cum Laude Poster Award)
[16] “An Efficient Method for Adapting Step-size Parameters of Primal-dual Hybrid Gradient Method in Application to Total Variation Regularization”T. Yokota, and H. HontaniAPSIPA-ASC, 2017.
[15] “A Robust PET Image Reconstruction using Constrained Non-negative Matrix Factorization”K. Kawai, J. Yamada, H. Hontani, T. Yokota, M. Sakata, and Y. KimuraAPSIPA-ASC, 2017.
[14] “Simultaneous Visual Data Completion and Denoising based on Tensor Rank and Total Variation Minimization and its Primal-dual Splitting Algorithm”T. Yokota, and H. HontaniCVPR, 2017.(poster, acceptance rate = 29.2%)
[13] “Restoration of Temporal Image Sequence from a Single Image Captured by a Correlation Image Sensor”K. Kawade, A. Wakita, T. Yokota, H. Hontani, and S. AndoVISAPP, 2017.(Best Student Paper Award)
[12] “Automatic detection of brachial artery in ultrasound images for a flow meditated dilation test”K. Sano, H. Masuda, K. Sano, H. Suzuki, T. Koyama, T. Yokota, and H. HontaniIFMIA, 2017.
[11] “Tensor Completion via Functional Smooth Component Deflation”T. Yokota, and A. CichockiICASSP, 2016.(poster, acceptance rate = 47.0%)
[10] “A fast automatic rank determination algorithm for noisy low-rank matrix completion”T. Yokota, and A. CichockiAPSIPA-ASC, 2015.
[9] “Smooth PARAFAC Decomposition for Tensor Completion”T. Yokota, and A. CichockiLow-rank Optimization and Applications, Bonn, Germany, Jun. 8-12, 2015.
[8] “Multilinear tensor rank estimation via sparse Tucker decomposition”T. Yokota, and A. CichockiSCIS&ISIS, 2014.(IEEE Computational Intelligence Society Japan Chapter Young Researcher Award)(Incentive Award from Japan Society of Fuzzy Theory and Intelligent Informatics )
[7] “Linked Tucker2 decomposition for flexible multi-block data analysis”T. Yokota, A. CichockiICONIP, 2014.
[6] “B-Spline Smoothing of Feature Vectors in Nonnegative Matrix Factorization” R. Zdunek, A. Cichocki, and T. YokotaICAISC, 2014.
[5] “Heteroscedastic Gaussian based Correction term for Fisher Discriminant Analysis and Its Kernel Extension”T. Yokota, T. Wakahara, and Y. YamashitaIJCNN, 2013.
[4] “Linked PARAFAC/CP Tensor Decomposition and Its Fast Implementation for Multi-block Tensor Analysis”T. Yokota, A. Cichocki, and Y. YamashitaICONIP, 2012.
[3] “EEG Beta Range Dynamics and Emotional Judgments of Face and Voices”K. Taniguchi-Hiyoshi, M. Kawasaki, T. Yokota, H. Bakardjian, H. Fukuyama, F. Vialatte, and A. CichockiIJCCI, Oct. 2012.
[2] “Support Vector Machine with Weighted Regularization”T. Yokota, and Y. YamashitaICONIP, Nov. 2011.
[1] “Quadratically Constrained Maximum A Posteriori Estimation for Binary Classifier”T. Yokota, and Y. YamashitaMLDM, Aug. 2011.