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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
PRMU, IBISML, IPSJ-CVIM |
2024-03-03 09:24 |
Hiroshima |
Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
Cardiac Detection in Non-Contrast CT and Application to Calcium Scoring Tetsuya Asakawa, Hiroki Shinoda (TUT), Takuya Togawa, Kazuki Shimizu (THC), Masaki Aono (TUT) PRMU2023-59 |
Coronary artery disease, one of the major causes of death in Japan, is said to be related to coronary artery calcifica- ... [more] |
PRMU2023-59 pp.47-52 |
PRMU, MVE, VRSJ-SIG-MR, IPSJ-CVIM |
2024-01-26 15:58 |
Kanagawa |
Keio Univ. (Hiyoshi Campus) |
An attempt to determine stenosis from coronary stretch images using deep learning Tetsuya Asakawa, Hiroki Shinoda, Yuta Fukatsu (TUT), Takuya Togawa, Kazuki Shimizu (THC), Masaki Aono (TUT) PRMU2023-49 |
Coronary artery stenosis, one of the most common heart diseases, is diagnosed by a human, which is a time-consuming and ... [more] |
PRMU2023-49 pp.50-55 |
MI, MICT |
2023-11-14 14:00 |
Fukuoka |
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Estimating the degree of coronary artery stenosis from non-contrast CT images using a 3D convolution model
-- Categorical approach -- Hiroki Shinoda, Tetsuya Asakawa (TUT), Kazuki Shimizu, Takuya Togawa, Kei Nomura (Toyohashi Heart Center), Masaki Aono (TUT) MICT2023-32 MI2023-25 |
In current medical images diagnosis, specialists take pictures of patients and search for the disease from the images. I... [more] |
MICT2023-32 MI2023-25 pp.29-32 |
MI |
2023-03-06 09:57 |
Okinawa |
OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Multi-label multi-class estimation of pathology in high-resolution chest CT images using SRGAN Tetsuya Asakawa, Riku Tsuneda, Yuki Sugimoto (TUT), Kazuki Shimizu, Takuyuki Komoda (THC), Masaki Aono (TUT) MI2022-76 |
The purpose of this research, three pathologies (thickening, calcification, and cavitation) were accurately estimated as... [more] |
MI2022-76 pp.14-19 |
MI |
2023-03-06 15:47 |
Okinawa |
OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Predicting disease from Chest-X-ray and Heart-CT images using Fine Tuning Yuya Kumagai, Hiroki Shinoda, Tetsuya Asakawa (TUT), Kazuki Shimizu, Takuyuki Komoda (THC), Masaki Aono (TUT) MI2022-91 |
[more] |
MI2022-91 pp.88-93 |
PRMU |
2022-10-21 16:25 |
Tokyo |
Miraikan - The National Museum of Emerging Science and Innovation (Primary: On-site, Secondary: Online) |
Heart Detection Method in Non-Contrast Chest CT Image and Application to Calcium Scoring Yuki Sugimoto, Tetsuya Asakawa (TUT), Kazuki Shimizu, Takuyuki Komoda (THC), Masaki Aono (TUT) PRMU2022-31 |
Coronary artery disease, one of the major causes of death in Japan, is said to be related to coronary artery calcificati... [more] |
PRMU2022-31 pp.50-55 |
MI |
2022-07-09 15:20 |
Hokkaido |
(Primary: On-site, Secondary: Online) |
Disease segmentation of 3D diagnostic images
-- Disease detection using CT data -- Tetsuya Asakawa, Riku Tsuneda, Yuki Sugimoto (TUT), Kazuki Shimizu, Takuyuki Komoda (THC), Masaki Aono (TUT) MI2022-47 |
Disease detection from medical images reinforce the judgment of doctors and medical engineers, and is expected to play a... [more] |
MI2022-47 pp.56-60 |
PRMU, IPSJ-CVIM |
2022-03-10 10:40 |
Online |
Online |
Medical Image Captioning with Information based on Medical Concepts Riku Tsuneda, Tetsuya Asakawa (TUT), Kazuki Shimizu, Takuyuki Komoda (THC), Masaki Aono (TUT) PRMU2021-64 |
Image Captioning for medical images is expected to augment the judgment of doctors and serve as a second opinion. Medica... [more] |
PRMU2021-64 pp.25-30 |
MI |
2021-07-09 14:00 |
Online |
Online |
Severity determination of chest CT data in tuberculosis patients using deep learning Tetsuya Asakawa, Riku Tsuneda (TUT), Kazuki Simizu, Takuyuki Komoda (THC), Masaki Aono (TUT) MI2021-19 |
The purpose of this study is to make accurate estimates for five labels (infiltrative, focal, tuberculoma, miliary, and ... [more] |
MI2021-19 pp.42-46 |
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