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All Technical Committee Conferences (Searched in: Recent 10 Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI | 2025-03-19 13:36 |
Kagawa | Kagawa International Conference Hall (Primary: On-site, Secondary: Online) |
Anomaly Region Detection by Progressive Mask Refinement using Diffusion Models Hiroki Tobise (NIT), Masahiro Hashimoto (Keio Univ.), Toshiaki Akashi (Juntendo Univ.), Hidekata Hontani (NIT)  MI2024-50 |
In this paper, we propose an unsupervised anomaly detection method using a diffusion model. The diffusion model encodes ... [more] | MI2024-50 pp.13-16 |
| 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) PRMU2024-36 |
In this paper, we propose an anomaly detection method that uses a diffusion model as an autoencoder. The diffusion model... [more] | PRMU2024-36 pp.18-23 |
| MI | 2023-03-06 10:23 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Computer-aided diagnosis of chest CT images for COVID-19 with lesion enhancement Yusuke Takateyama (TUAT), Masahiro Hashimoto (Keio Univ.), Yoshito Otake (NAIST), Toshiaki Akashi (Juntendo Univ.), Akinobu Shimizu (TUAT) MI2022-78 |
(To be available after the conference date) [more] | MI2022-78 pp.24-25 |
| MI | 2023-03-06 13:28 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Segmentation of Infected Regions from Chest CT Scans of COVID-19 Cases using Average Template Kai Liu, Masahiro Oda, Tong Zheng, Yuichiro Hayashi (Nagoya Univ.), Yoshito Otake (NAIST), Masahiro Hashimoto (Keio Univ.), Toshiaki Akashi, Shigeki Aoki (Juntendo Univ.), Kensaku Mori (Nagoya Univ.) MI2022-81 |
[more] | MI2022-81 pp.40-45 |
| MI | 2023-03-06 16:51 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Synthesizing COVID-19 CT Images with Generative Adversarial Networks Ryo Kawasaki (TUAT), Masahiro Hashimoto (Keio Univ.), Yoshito Otake (NAIST), Toshiaki Akashi (Juntendo Univ.), Akinobu Shimizu (TUAT) MI2022-95 |
(To be available after the conference date) [more] | MI2022-95 pp.111-112 |
| 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 |
| MICT, MI | 2022-11-18 14:00 |
Aichi | Nagoya Institute of Technology | Extrapolation of partial X-ray image for prediction of whole body musculoskeletal structure Weiqi Zhang, Yi Gu, Yoshito Otake, Soufi Mazen (NAIST), Keisuke Uemura (Osaka Univ), Masaki Takao (Ehime Univ), Toshiaki Akashi (Juntendo Univ), Kensaku Mori (Nagoya Univ/NII), Kento Aida (NII), Nobuhiko Sugano (Osaka Univ), Yoshinobu Sato (NAIST) MICT2022-38 MI2022-67 |
Image defects and partial disorders are common problems in medical imaging. Image inpainting and extrapolation are helpf... [more] | MICT2022-38 MI2022-67 pp.24-28 |
| MICT, MI | 2022-11-18 14:25 |
Aichi | Nagoya Institute of Technology | Development of a Statistical Model for Predicting Aging Change in Spine and Pelvis Based on Landmarks Detected in a Large Scale Torso CT Image Database Yuga Shimomoto, Yoshito Otake, Tomoki Hakotani, Mazen Soufi (NAIST), Hideki Shigematu (Nara Med. Univ.), Keisuke Uemura (Osaka Univ.), Masaki Takao (Ehime Univ.), Toshiaki Akashi (Juntendo Univ.), Kensaku Mori (Nagoya Univ./NII), Kento Aida (NII), Nobuhiko Sugano (Osaka Univ.), Yoshinobu Sato (NAIST) MICT2022-39 MI2022-68 |
One way to describe variations in skeletal shape is a statistical shape model (SSM), which statistically analyzes organ ... [more] | MICT2022-39 MI2022-68 pp.29-32 |
| 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 10:26 |
Online | Online | MI2021-54 |
[more] | MI2021-54 pp.43-44 |
| MI | 2022-01-26 11:05 |
Online | Online | Study on automatic generation of COVID-19 related radiology reports from chest CT images Shinji Okazaki, Yuichiro Hayashi, Masahiro Oda (Nagoya Univ.), Masahiro Hashimoto, Masahiro Jinzaki (Keio Univ.), Toshiaki Akashi, Shigeki Aoki (Juntendo Univ.), Kensaku Mori (Nagoya Univ./NII) MI2021-57 |
In this paper, we describe a study on automatic generation of COVID-19 related radiology reports from chest CT images. T... [more] | MI2021-57 pp.49-54 |
| MI | 2021-03-16 09:00 |
Online | Online | Lung segmentation of thoracic CT volumes by combining slice-wise with pixel-wise classification Takahito Haruishi, Atsushi Saito (TUAT), Masahiro Hashimoto (Keio University), Yoshito Otake (NAIST), Toshiaki Akashi (Juntendo University), Akinobu Shimizu (TUAT) MI2020-63 |
[more] | MI2020-63 pp.72-73 |
| MI | 2021-03-16 09:45 |
Online | Online | MI2020-66 |
In this paper, we propose a method for automatically classifying COVID-19 cases from CT images of lung fields. Currently... [more] | MI2020-66 pp.82-86 |
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