Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
PRMU, IPSJ-CVIM, VRSJ-SIG-MR, MVE |
2025-01-21 13:35 |
Fukuoka |
(Primary: On-site, Secondary: Online) |
Anomaly Region Detection in Medical Images using Diffusion Models with Simplex Noise and Progressive Mask Refinement Hiroki Tobise (NIT), Masahiro Hashimoto (Keio Univ.), Toshiaki Akashi (Juntendo Univ.), Hidekata Hontani (NIT) |
[more] |
|
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 09:17 |
Okinawa |
OKINAWAKEN SEINENKAIKAN (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 10:05 |
Okinawa |
OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Post-hoc Rotational Equivariantization of Large Scale Neural Network Model and Its Application Kotaro Ogawa, Toyohiro Maki, Hidekata Hontani (NIT) MI2023-35 |
In this study, we propose a rigid body registration method that works even for spatial deviations that involve large rot... [more] |
MI2023-35 pp.19-20 |
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 |
2024-03-04 15:58 |
Okinawa |
OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Representations obtained by self-supervised learning of hierarchical ViT to discriminate between benign and malignant breast tumors Akiomi Ishikawa (NIT), Kouji Arihiro (HIrosima Univ), Hidekata Hontani (NIT) MI2023-88 |
In this paper, I report a method to apply the representation of pathological microscopic images obtained by self-supervi... [more] |
MI2023-88 pp.184-185 |
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 10:45 |
Okinawa |
OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Report on MICCAI 2022 Hayato Itoh, Masahiro Oda, Chen Shen, Cheng Wang (Nagoya Univ.), Kanta Miura (Tohoku Univ.), Junya Sato (Osaka Univ.), Yoshito Otake (NAIST), Ryoma Bise (Kyushu Univ.), Ryo Furukawa (Kindai Univ.), Hidekata Hontani (NITech), Yoshitaka Masutani (Tohoku Univ.), Kensaku Mori (Nagoya Univ.) MI2022-79 |
In this paper, we overview the outlines of MICCAI 2022’s main conference sessions and satellite workshops. Several inter... [more] |
MI2022-79 pp.26-37 |
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 |
2022-07-08 14:00 |
Hokkaido |
(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 |
2022-01-26 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 |
2022-01-26 16:00 |
Online |
Online |
Report on MICCAI 2021 Hayato Itoh, Masahiro Oda, Chen Shen (Nagoya Univ.), Yoshito Otake (NAIST), Shouhei Hanaoka (Tokyo Univ.), Ken'ichi Morooka (Okayama Univ.), Hidekata Hontani (NITech), Ryo Furukawa, Yoshitaka Masutani (Hiroshima City Univ.), Kensaku Mori (Nagoya Univ.) MI2021-67 |
In this paper, the outlines of MICCAI 2021 main conference sessions and workshops are introduced. A few interesting repo... [more] |
MI2021-67 pp.89-99 |
MI |
2022-01-27 13:54 |
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, 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 |