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All Technical Committee Conferences (Searched in: All Years)
| 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 |
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| 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 |
| PRMU, IPSJ-CVIM | 2022-03-11 16:10 |
Online | Online | Spatial attention and parallel convolution for Real-time segmentation Yuki Sugimoto, Masaki Aono (TUT) PRMU2021-86 |
Semantic segmentation is an image recognition technique that classifies all objects and backgrounds by pixel in images. ... [more] | PRMU2021-86 pp.163-168 |
| 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 |
| MI | 2021-03-16 09:15 |
Online | Online | Tuberculosis in Chest CT Image Analysis based on multi-axis projections using Deep learning Tetsuya Asakawa, Masaki Aono (Toyohashi Univ) MI2020-64 |
The purpose of this research is to make accurate estimates for the six labels (Left affected, Right affected, Light ple... [more] | MI2020-64 pp.74-79 |
| PRMU, IPSJ-CVIM | 2021-03-04 09:30 |
Online | Online | Automatic 3D Mesh Generation by Using Extended Attentive Normalization Yuta Fukatsu, Masaki Aono (TUT) PRMU2020-69 |
In recent years, research on conditional image generation using GANs of the type where conditions are given by class lab... [more] | PRMU2020-69 pp.1-6 |
| PRMU, IPSJ-CVIM | 2021-03-04 10:00 |
Online | Online | Saliency Detection by Extended Attention and its Application to Image Synthesis Ryosuke Yamauchi, Masaki Aono (TUT) PRMU2020-71 |
In recent years, there has been much research on Style Transfer and Saliency Detection. Style Transfer is a task to sy... [more] |
PRMU2020-71 pp.13-18 |
| PRMU, IPSJ-CVIM | 2021-03-04 14:25 |
Online | Online | Leveraging Human Pose Estimation Model for Sports Video Classification Soichiro Sato, Masaki Aono (TUT) PRMU2020-76 |
In this paper, we propose a motion classification method of sports videos based on a posture estimation model.Specifical... [more] | PRMU2020-76 pp.41-46 |
| PRMU, IPSJ-CVIM | 2021-03-04 16:20 |
Online | Online | VQA for Medical Image Data based on Image Feature Extraction and Fusion Hideo Umada, Masaki Aono (TUT) PRMU2020-81 |
In recent years, there has been a remarkable growth in research on deep learning in the fields of computer vision and na... [more] | PRMU2020-81 pp.71-76 |
| PRMU, IPSJ-CVIM | 2021-03-05 14:25 |
Online | Online | Semantic Segmentation based on MobileNet Extended with FPN Yuki Sugimoto, Masaki Aono (TUT) PRMU2020-91 |
Semantic Segmentation is attracting attention in autonomous driving, but high-precision models require a huge amount of ... [more] | PRMU2020-91 pp.127-132 |
| PRMU | 2019-10-18 16:00 |
Tokyo | Partial Shape Similarity Search using Topology of 3D CAD Models Wataru Iwabuchi, Masaki Aono (TUT) PRMU2019-40 |
In recent years, 3D models are used in various fields. Accordingly, the amount of 3D shape models available on the Inter... [more] | PRMU2019-40 pp.47-52 |
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| PRMU, BioX | 2019-03-18 15:00 |
Tokyo | Reali-time Object Detection based on SSD Yuya Yamashige, Masaki Aono (TUT) BioX2018-60 PRMU2018-164 |
In recent years, attention has been paid to developing object detection methods from images, based on deep learning. In ... [more] | BioX2018-60 PRMU2018-164 pp.181-186 |
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| IE, ITE-ME, ITE-AIT [detail] | 2018-10-19 10:00 |
Nagasaki | Compositional Image Attention with Tree LSTMs for Grounding Textual Phrases Ko Endo, Masaki Aono (TUT), Eric Nichols (HRI-JP) IE2018-45 |
[more] | IE2018-45 pp.7-12 |
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| PRMU, IBISML, IPSJ-CVIM [detail] | 2018-09-21 09:30 |
Fukuoka | Semantic Segmentation of Aerial Images by Using Fully Convolutional Network Incorporating Dilated Convolution Takafumi Taguchi, Masaki Aono (TUT) PRMU2018-54 IBISML2018-31 |
[more] | PRMU2018-54 IBISML2018-31 pp.125-130 |
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