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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI | 2024-03-03 09:05 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Generation of Counterfactual Pathology Images of Malignant Lymphoma using Diffusion Models Ryoichi Koga, Tatsuya Yokota (NIT), Kouichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (Nagoya Univ.), Hidekata Hontani (NIT)  MI2023-30 |
Malignant lymphoma has more than 70 subtypes. In the pathological diagnosis, a pathological image is observed to identif... [more] | MI2023-30 pp.1-2 |
| MI | 2024-03-03 10:17 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Electric field regression from head MR image by transformers for TMS Toyohiro Maki, Tatsuya Yokota, Akimasa Hirata, Hidekata Hontani (NIT) MI2023-36 |
Transcranial Magnetic Stimulation (TMS) is a non-invasive stimulation method by electric field induced by a coil placed ... [more] | MI2023-36 pp.21-24 |
| MI | 2024-03-03 16:42 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Using Label Uncertainty for Learning Cell Nuclei Type Classifier with Strongly Noisy Supervised Signals Shingo Koide, Mauricio Kugler, Tatsuya Yokota (NIT), Koichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (Nagoya Univ.), Hidekata Hontani (NIT) MI2023-57 |
In this study, we construct a type classifier for cell nuclei of malignant lymphomas. Labelling by type is not easy, eve... [more] | MI2023-57 pp.79-80 |
| MI | 2024-03-04 09:36 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Overfitting Prevention for PET Image Reconstruction using Early Stopping of Deep Image Prior based on Unbiased Risk Estimator Kaito Matsumura, Hidekata Hontani (NIT), Muneyuki Sakata (TMIG), Yuichi Kimura (KDU), Tatsuya Yokota (NIT) MI2023-65 |
In recent years, methods for PET image reconstruction using Deep Image Prior (DIP) have been actively studied. In PET im... [more] | MI2023-65 pp.106-108 |
| MI | 2024-03-04 11:10 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Identification of follicle segmentation and subtype in a lymph node HE-stained image based on the set of cell nuclei Mizuki Moribe, Tatsuya Yokota (NIT), Koichi Oshima, Hiroaki Miyoshi, Miharu Nagaishi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (NU), Hidekata Hontani (NIT) MI2023-72 |
In this paper, we report on a method for follicle segmentation and the identification of malignant lymphoma subtypes usi... [more] | MI2023-72 pp.131-132 |
| MI | 2023-09-08 10:05 |
Osaka | (Primary: On-site, Secondary: Online) |
[Short Paper]
Construction of Cell Nucleus Classifier using Complementary-Label Learning towards the Quantification of Grading for Follicular Lymphoma Ryoichi Koga, Mauricio Kugler, Tatsuya Yokota (NIT), Kouichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (Nagoya Univ.), Hidekata Hontani (NIT) MI2023-14 |
In this paper, we report the cell type classification from a pathological image toward the subtype classification of mal... [more] | MI2023-14 pp.1-2 |
| MI | 2023-03-06 17:04 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Rotation-Equivariant CNN for Medical Image Processing Applications Ryota Ogino, Kugler Mauricio, Tatsuya Yokota, Hidekata Hontani (NITech) MI2022-96 |
In this study, we report an attempt to use a Rotation-Equivariant CNN to organize image data whose rotation direction an... [more] | MI2022-96 pp.113-114 |
| MI | 2023-03-06 17:17 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Accuracy Improvement of Annotation Label in Microscopic Pathological Images Hirotaka Yasuma, Kugler Mauricio, Tatsuya Yokota (NiTech), Kouji Arihiro (Hiroshima Univ.), Hidekata Hontani (NiTech) MI2022-97 |
[more] | MI2022-97 pp.115-116 |
| MI | 2023-03-06 17:56 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Generation of Counterfactual Images towards the Construction of Quantitatively Criteria in Malignant Lymphoma Ryoichi Koga, Mauricio Kugler, Tatsuya Yokota (NIT), Kouichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi (KU), Noriaki Hashimoto, Ichiro Takeuchi (NU), Hidekata Hontani (NIT) MI2022-100 |
In pathological diagnosis of malignant lymphoma, a H&E-staind pathological image is observed to identify the subtype. Ho... [more] | MI2022-100 pp.123-124 |
| MI | 2023-03-07 17:16 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Anomaly Region Detection for Chest CT Images based on Probability Density Estimation Hiroki Tobise, Mauricio Kugler, Tatsuya Yokota (NIT), Masahiro Hashimoto (Keio Univ.), Yoshito Otake (NAIST), Toshiaki Akashi (Juntendo Univ.), Akinobu Shimizu (TUAT), Hidekata Hontani (NIT) MI2022-127 |
[more] | MI2022-127 pp.215-216 |
| MI | 2022-01-26 10:13 |
Online | Online | [Short Paper]
Abnormality Detection for Covid-19 Chest CT Images by Dimensionality Reduction Based on Contrastive Learning Hiroki Tobise, Kugler Mauricio, Tatsuya Yokota (NITech), Masahiro Hashimoto (Keio Univ.), Yoshito Otake (NAIST), Toshiaki Akashi (Juntendo Univ.), Akinobu Shimizu (TUAT), Hidekata Hontani (NITech) MI2021-53 |
In this article, we propose a method that detects anomaly regions in chest CT images for the aid of Covid-19 diagnosis. ... [more] | MI2021-53 pp.41-42 |
| MI, MICT [detail] | 2021-11-05 11:05 |
Online | Online | [Short Paper]
Description of microvessel structures in 3D reconstructed microscopic pathological images of pancreatic cancer Yuka Ishimaki, Tatsuya Yokota, Kugler Mauricio (NITech), Kenoki Ohuchida (KU), Hidekata Hontani (NITech) MICT2021-33 MI2021-31 |
In this manuscript, we propose a method that segments microvascular regions in a 3D pathological image. For this purpose... [more] | MICT2021-33 MI2021-31 pp.26-27 |
| MI | 2021-07-09 11:00 |
Online | Online | [Short Paper]
Construction of Subtype Classifier for Malignant Lymphoma based on H&E-stained Images using Immuno-stainning Data Yuki Hirono (NIT), Noriaki Hashimoto (RIKEN), Kugler Mauricio, Tatsuya Yokota (NIT), Miharu Nagaishi (Kurume Univ.), Hiroaki Miyoshi, Koichi Oshima (Kurume Univ./JSP), Ichiro Takeuchi (NIT/RIKEN), Hidekata Hontani (NIT) MI2021-16 |
In pathological diagnosis of malignant lymphoma, a HE image is observed at first and then a set of immunostained images ... [more] | MI2021-16 pp.31-32 |
| MI | 2021-05-17 10:00 |
Online | Online | [Short Paper]
Regression of Induced Electric Field for TMS by using Neural Network and Governing Equation Toyohiro Maki (NITech), Yoshikazu Ugawa, Takenobu Murakami (Fukushima Medical Univ.), Tatsuya Yokota, Akimasa Hirata, Hidekata Hontani (NITech) MI2021-1 |
TMS (Transcranial Magnetic Stimulation) is a method which stimulate the neurons in the brain by using a coil. Since stim... [more] | MI2021-1 pp.1-2 |
| PRMU | 2020-12-17 11:00 |
Online | Online | Fast algorithm for low-rank tensor completion in multi-way delay embedded space Ryuki Yamamoto, Tatsuya Yokota (Nagoya Institute of Tech.), Akira Imakura (Univ. of Tsukuba), Hidekata Hontani (Nagoya Institute of Tech.) PRMU2020-42 |
In recent years, low-rank tensor completion using delay embedding has been an important technique. In order to capture s... [more] | PRMU2020-42 pp.24-29 |
| MI | 2020-09-03 13:10 |
Online | Online | [Invited Talk]
Manifold modeling in embedded space for image restoration Tatsuya Yokota (Nitech) MI2020-27 |
In this invited talk, I will discuss convolutional neural networks, which have achieved remarkable results in various im... [more] | MI2020-27 pp.43-44 |
| MI | 2020-01-30 10:00 |
Okinawa | OKINAWAKEN SEINENKAIKAN | Construction of Basis Vectors for Representation of Immunostaining Combination by Non-negative Matrix Decomposition Kaho Ko, Noriaki Hashimoto, Tatsuya Yokota (NITech), Masato Nakaguro, Kei Kohno, Shigeo Nakamura (NUH), Ichiro Takeuchi, Hidekata Hontani (NITech) MI2019-99 |
In this paper, we propose a method that constructs a set of basis vectors for representing combination of immunostaining... [more] | MI2019-99 pp.151-154 |
| MI | 2020-01-30 10:10 |
Okinawa | OKINAWAKEN SEINENKAIKAN | Mutual stain transfer among differently stained pathological images with Extraction of Common Image Features Hideo Adachi, Mauricio Kugler (NIT), Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume (Kyushu Univ.), Tatsuya Yokota, Hidekata Hontani (NIT) MI2019-100 |
[more] | MI2019-100 pp.155-158 |
| MI | 2020-01-30 11:00 |
Okinawa | OKINAWAKEN SEINENKAIKAN | High precision metal artifacts reduction in X-ray CT images by Deep Image Prior and sinogram normalization Hiroya Satake, Tatsuya Yokota (NIT), Yoshito Otake, Yoshinobu Sato (NAIST), Hidekata Hontani (NIT) MI2019-103 |
In this paper, we propose a method to improve the normalization accuracy of sinogram by using DeepImage Prior to remove ... [more] | MI2019-103 pp.169-174 |
| MI | 2020-01-30 13:25 |
Okinawa | OKINAWAKEN SEINENKAIKAN | Extracting and Visualization of Essential Features for Staining Translation of Pathological Images Ryoichi Koga, Noriaki Hashimoto, Tatsuya Yokota (NIT), Masato Nakaguro, Kei Kohno, Shigeo Nakamura (NUI), Ichiro Takeuchi, Hidekata Hontani (NIT) MI2019-116 |
In this manuscript, we propose a method for stain translation of pathology images. When one constructs a computer aided ... [more] | MI2019-116 pp.215-218 |
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