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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 9 of 9  /   
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   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
 Results 1 - 9 of 9  /   
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