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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML | 2024-12-20 10:50 |
Hokkaido | Lecture room 1 (D101), Graduate School of Environmental Science (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Active learning considering test distribution with Gaussian process regression model Yoshito Okura (Nagoya Univ.), Shion Takeno (Nagoya Univ./RIKEN), Yu Inatsu (NITech), Tatsuya Aoyama, Tomonari Tanaka, Satoshi Akahane (Nagoya Univ.), Hiroyuki Hanada, Noriaki Hashimoto (RIKEN), Taro Murayama, Lee Hanju, Shinya Kojima (DENSO), Ichiro Takeuchi (Nagoya Univ./RIKEN)  IBISML2024-37 |
Active learning is a method to construct a model with high prediction accuracy with a small number of data by adaptively... [more] | IBISML2024-37 pp.41-48 |
| IBISML | 2024-12-21 15:30 |
Hokkaido | Lecture room 1 (D101), Graduate School of Environmental Science (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Distributionally Robust Training Instances Selection with Guaranteed Model Performance Tomonari Tanaka (Nagoya Univ.), Hiroyuki Hanada (RIKEN), Hanting Yang (Nagoya University), Tatsuya Aoyama (Nagoya Univ.), Yu Inatsu (NITech), Satoshi Akahane, Yoshito Okura (Nagoya Univ.), Noriaki Hashimoto (RIKEN), Taro Murayama, Lee Hanju, Shinya Kojima (DENSO), Ichiro Takeuchi (Nagoya Univ./RIKEN) IBISML2024-53 |
In a problem setting where the data distribution differs between the development and operational phases, there exists a ... [more] | IBISML2024-53 pp.151-158 |
| IBISML, NC, IPSJ-BIO, IPSJ-MPS [detail] | 2024-06-20 15:50 |
Okinawa | OIST (Okinawa) | Distributionally Robust Safe Sample Screening and Its Application to Infinite-width Deep Neural Networks Tatsuya Aoyama (Nagoya Univ.), Hiroyuki Hanada (RIKEN), Satoshi Akahane, Yoshito Okura, Tomonari Tanaka (Nagoya Univ.), Yu Inatsu (NITech), Noriaki Hashimoto (RIKEN), Taro Murayama, Lee Hanju, Shinya Kojima (DENSO), Ichiro Takeuchi (Nagoya Univ.) NC2024-10 IBISML2024-10 |
In machine learning, handling large datasets has been problematic in computational resources. For this issue, safe sampl... [more] | NC2024-10 IBISML2024-10 pp.67-72 |
| MI | 2024-03-03 09:05 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Okinawa, Online) (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 09:17 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Okinawa, Online) (Primary: On-site, Secondary: Online) |
[Short Paper]
Valid p-value for critical instances in multiple instance learning Noriaki Hashimoto (RIKEN), Daiki Miwa (Nitech), Kosei Sumida (Nagoya Univ.), Hiroyuki Hanada (RIKEN), Hiroaki Miyoshi (Kurume Univ.), Jun Sakuma (Tokyo Tech/RIKEN), Hidekata Hontani (Nitech), Koichi Ohshima (Kurume Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN) MI2023-31 |
(To be available after the conference date) [more] | MI2023-31 pp.3-6 |
| MI | 2024-03-03 16:42 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Okinawa, Online) (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 11:10 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Okinawa, Online) (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 | (Osaka, Online) (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 17:56 |
Okinawa | OKINAWA SEINENKAIKAN (Okinawa, Online) (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 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-03 16:25 |
Hokkaido | Future University Hakodate (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Fast Identification of Possible Model Parameter Update for Low-Rank Update of Training Data Hiroyuki Hanada, Noriaki Hashimoto (RIKEN), Kouichi Taji, Ichiro Takeuchi (Nagoya Univ.) PRMU2022-123 IBISML2022-130 |
Machine learning methods often require re-training the training dataset with low-rank modifications (small number of ins... [more] | PRMU2022-123 IBISML2022-130 pp.347-354 |
| MI | 2022-07-08 14:00 |
Hokkaido | (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Cell type-specific tumor degree estimation in malignant lymphoma pathology images Hiroki Masuda (NITech), Noriaki Hashimoto (RIKEN), Yusuke Takagi (NITech), Hiroyuki Hanada (RIKEN), Hiroaki Miyoshi, Kensaku Sato, Koichi Oshima (Kurume Univ.), Hidekata Hontani (NITech), Ichiro Takeuchi (Nagoya Univ./RIKEN) MI2022-32 |
In the pathological diagnosis flow of malignant lymphoma, a type of blood cancer, it is important to identify the type o... [more] | MI2022-32 pp.1-6 |
| MI | 2022-01-27 13:54 |
Online | Online (Online) | [Short Paper]
Case-based Similar Image Retrieval for Pathological Images of Malignant Lymphoma Using Deep Metric Learning Noriaki Hashimoto (RIKEN), Yusuke Takagi, Hiroki Masuda (NITech), Hiroaki Miyoshi, Kei Kohno, Miharu Nagaishi, Kensaku Sato, Koichi Ohshima (Kurume Univ.), Hidekata Hontani (NITech), Ichiro Takeuchi (NITech/RIKEN) MI2021-78 |
We propose a novel method of case-based similar image retrieval for histopathological images of malignant lymphoma. We e... [more] | MI2021-78 pp.144-145 |
| MI | 2021-07-09 11:00 |
Online | 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 | 2020-01-30 10:00 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Okinawa) | 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 13:25 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Okinawa) | 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 |
| PRMU, MI, IPSJ-CVIM [detail] | 2019-09-04 16:20 |
Okayama | (Okayama) | Domain-adversarial multiple instance learning for subtype classification of malignant lymphoma Daisuke Fukushima, Ryoichi Koga, Noriaki Hashimoto, Kaho Ko (Nagoya Inst. of Tech), Masato Nakaguro, Kei Kohno, Shigeo Nakamura (Nagoya Univ. Hospital), Hidekata Hontani (Nagoya Inst of Tech), Ichiro Takeuchi (Nagoya Inst. of Tech/RIKEN/NIMS) PRMU2019-15 MI2019-34 |
We classify subtypes of malignant lymphoma using convolutional neural network with digital pathological images as input ... [more] | PRMU2019-15 MI2019-34 pp.19-24 |
| MI | 2019-01-22 15:05 |
Okinawa | (Okinawa) | [Short Paper]
Study on subtype classification of malignant lymphoma using immunostaining information Noriaki Hashimoto, Kaho Ko, Daisuke Fukushima, Tatsuya Yokota (Nagoya Inst. of Tech.), Masato Nakaguro, Kei Kohno, Shigeo Nakamura (Nagoya Univ. Hospital), Ichiro Takeuchi (Nagoya Inst. of Tech./RIKEN/NIMS), Hidekata Hontani (Nagoya Inst. of Tech.) MI2018-83 |
[more] | MI2018-83 pp.95-96 |
| MI | 2015-03-02 10:05 |
Okinawa | Hotel Miyahira (Okinawa) | Deformation and correction of 2D pathology images of brain via macro images Takuya Tanaka, Takashi Ohnishi, Yuka Nakamura, Noriaki Hashimoto, Hideaki Haneishi (Chiba Univ.) MI2014-58 |
Although, MRI is mainly used for the diagnosis of brain tumor, it's difficult to identify infiltration area of tumor fro... [more] | MI2014-58 pp.29-33 |
| MI | 2014-01-27 10:50 |
Okinawa | Bunka Tenbusu Kan (Okinawa) | Distortion correction and synthesis of 2D histology images of brain tumor using macro images Toru Tanaka, Takashi Ohnishi (Chiba Univ.), Yukako Yagi, Noriaki Hashimoto (MGH/HMS), Jennie Taylor (MGH), Matija Snuderl (NYU), Hideaki Haneishi (Chiba Univ.) MI2013-96 |
For detailed analysis and diagnosis of glioblastoma (GBM), it is required to compare pathological images with MR images ... [more] | MI2013-96 pp.219-224 |
| AP | 2013-04-19 10:10 |
Hyogo | Kwansei Gakuin Univ. (Hyogo) | Hepta-band Monopole Antenna for mobile terminals Takashi Uemura, Noriaki Hashimoto, Tadahiko Maeda (Ritsumeikan Univ.) AP2013-11 |
[more] | AP2013-11 pp.61-64 |
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