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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI | 2023-07-03 13:00 |
Miyagi | Tohoku Univ. Sakura Hall | [Special Talk]
Transition of Medical Imaging Koichi Ito (Tohoku Univ.)  MI2023-10 |
Over the past decade, research in medical image processing has dramatically changed. In particular, feature extraction u... [more] | MI2023-10 p.11 |
| 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 | 2023-03-07 16:13 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Classification of endoscope images with specular reflection using CNN Shun Katsuyama, Masashi Fujii (Tottori Univ.), Kazutake Uehara (Yonago Coll.), Masaru Ueki, Hajime Isomoto, Katsuya Kondo (Tottori Univ.) MI2022-123 |
The endoscopic training system is required that checks whether the inspection points have been taken. In this report, we... [more] | MI2022-123 pp.199-204 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 11:05 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
On the Effectiveness of Formula-Driven Supervised Learning for Medical Image Tasks Ryuto Endo, Shuya Takahashi, Eisaku Maeda (TDU) PRMU2022-71 IBISML2022-78 |
Deep learning for image information processing often uses manually maintained natural image data. However, these data ha... [more] | PRMU2022-71 IBISML2022-78 pp.71-75 |
| EST | 2023-01-27 11:40 |
Okinawa | (Primary: On-site, Secondary: Online) |
Radar Detection of Multiple Walking People Using Image-Processing Technique and Generalized Likelihood Ratio Test Jianxuan Yang, Jianxin Yi (Wuhan Univ.), Takuya Sakamoto (Kyoto Univ.), Xianrong Wan (Wuhan Univ.) EST2022-95 |
This study presents a detection algorithm of extended radar targets using image features and achieves the detection of m... [more] | EST2022-95 pp.108-111 |
| SC | 2022-05-27 11:20 |
Online | Online | Developing a Secure Streaming System of Clinic Site for Medical Education Sinan Chen, Masahide Nakamura, Kenji Sekiguchi (Kobe Univ.) SC2022-5 |
Clinical practice in the outpatient consultation room is restricted due to the COVID-19 control measures, resulting in t... [more] | SC2022-5 pp.25-30 |
| EST | 2022-01-28 11:00 |
Online | Online | Blood Vessel Structure Analysis using a Simulation Model for the Purpose of Polyp Shape Recovery from Endoscopic Images Shusuke Kato, Hiroyasu Usami, Akihiko Okazaki, Yuji Iwahori (Chubu Univ.), Ogasawara Naotaka, Kunio Kasugai (Aichi Medical Univ.) EST2021-83 |
In recent years, the incidence of colorectal cancer in Japan has been on the rise. It is essential to realize a medical ... [more] | EST2021-83 pp.130-135 |
| MI | 2022-01-27 11:10 |
Online | Online | [Fellow Memorial Lecture]
[IEICE Fellow Special Lecture] Human anatomical structure analysis by medical image processing and its application to diagnostic and therapeutic procedures assistance
-- Look back 30 years of research experiences and predict future -- Kensaku Mori (Nagoya Univ.) MI2021-74 |
This paper outlines my IEICE Fellow Special Lecture entitled human anatomical structure analysis by medical image proces... [more] | MI2021-74 pp.127-132 |
| 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 | 2020-12-18 16:20 |
Online | Online | [Short Paper]
Case Discrimination: Self-supervised Learning for classification of Medical Image Haohua Dong, Yutaro Iwamoto (Ritsumeikan Univ.), Xianhua Han (Yamaguchi Univ.), Lanfen Lin (Zhejiang Univ.), Hongjie Hu, Xiujun Cai (Sir Run Run Shaw Hospital), Yen-Wei Chen (Ritsumeikan Univ.) PRMU2020-64 |
Deep Learning provides exciting solutions to problems in medical image analysis and is regarded as a key method for futu... [more] | PRMU2020-64 pp.151-155 |
| PRMU | 2020-10-09 10:45 |
Online | Online | Trial of three-dimensional extraction and classification of cell regions in the heart Asuma Takematsu, Masahiro Migita, Masashi Toda, Yuichiro Arima (Kumamoto Univ.) PRMU2020-21 |
Analysis of cardiomyocytes is urgently needed to elucidate the pathophysiology of heart disease. Cardiomyocytes are char... [more] | PRMU2020-21 pp.15-19 |
| MI | 2020-09-03 15:10 |
Online | Online | Medical Image Processing on Nagoya University Super Computer System "Flow" Satoshi Ohshima, Masahiro Oda, Takahiro Katagiri, Kensaku Mori (Nagoya Univ.) MI2020-32 |
New supercomputer named "Flow" began service at July 1st, 2020 at Information Technology Center of Nagoya University. "F... [more] | MI2020-32 pp.69-74 |
| SC | 2020-05-29 15:30 |
Online | Online | [Poster Presentation]
Tumor detection from colonoscopy Whole Slice Images By Deep Learning Cherubin Mugisha, Incheon Paik (School of Computer Science and Engineering) |
Image semantic segmentation is a technique of segregating an image into many parts. The goal of this research was to use... [more] | |
| MI | 2020-01-29 10:15 |
Okinawa | OKINAWAKEN SEINENKAIKAN | Analysis of disease classification and musculoskeletal anatomy using medical images and radiology reports in a large-scale medical image database Shuhei Honda, Yoshito Otake (NAIST), Masaki Takao (Osaka Univ.), Eiji Aramaki, Shuntaro Yada, Yuta Hiasa (NAIST), Kento Aida, Shinichi Sato (NII), Akihiro Nishie (Kyushu Univ.), Nobuhiko Sugano (Osaka Univ.), Yoshinobu Sato (NAIST) MI2019-69 |
Recently, the environment for the analysis of large databases, such as the large-scale medical image database, have been... [more] | MI2019-69 pp.19-22 |
| ITS, IE, ITE-MMS, ITE-HI, ITE-ME, ITE-AIT [detail] | 2019-02-19 16:30 |
Hokkaido | Hokkaido Univ. | A Fundamental Study on Laparoscopic Image Region Segmentation Based on Texture Analysis by Regions Norifumi Kawabata (Nagoya Univ.), Toshiya Nakaguchi (Chiba Univ.) |
Most of image region segmentation studies can be divided to both subjective method by assessors and objective method by ... [more] | |
| MBE, NC (Joint) |
2018-03-13 11:15 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Application of U-Net to spine image extraction in CT image Mikoto Kamata, Masayuki Kikuchi (Tokyo Univ.of Tech.), Hayaru Shouno (Univ. of Electro-Communications.), Isao Hayashi (Kansai Univ.), Kunihiko Fukushima (Fuzzy Logic Systems Inst.) NC2017-81 |
In this study, we aimed at automatic extraction of spinal parts in CT images using deep learning as a foothold for autom... [more] | NC2017-81 pp.81-84 |
| ITS, IE, ITE-MMS, ITE-HI, ITE-ME, ITE-AIT [detail] | 2018-02-15 15:00 |
Hokkaido | Hokkaido Univ. | A Fundamental Study on Medical Image Diagnosis for Automatic Detection of Coded Defect Region Information Norifumi Kawabata, Toshiya Nakaguchi (Chiba Univ.) ITS2017-74 IE2017-106 |
The coded defect and degradation in the medial imaging field is each differenced for characteristics, nature, and status... [more] | ITS2017-74 IE2017-106 pp.77-82 |
| MI | 2017-01-18 11:22 |
Okinawa | Tenbusu Naha | Automated abdominal lymph node detection from 3D CT volumes using Structured Random Forest Yutaka Hoshiyama, Holger R. Roth, Masahiro Oda (Nagoya Univ.), Yoshihiko Nakamura (NIT), Kazunari Misawa (Aichi Cancer Center Hospital), Michitaka Fujiwara, Kensaku Mori (Nagoya Univ.) MI2016-76 |
In this paper, we report a study on automated lymph node detection method from 3D abdominal CT volumes using the Structu... [more] | MI2016-76 pp.23-28 |
| MI | 2017-01-18 14:15 |
Okinawa | Tenbusu Naha | GPU Programming for MIST Library Hirohisa Oda, Masahiro Oda (Nagoya Univ.), Takayuki Kitasaka (Aichi. Inst. Tech.), Kensaku Mori (Nagoya Univ.) MI2016-106 |
In recent years, there is a trend toward the development of high-speed computation techniques due to the improvement in ... [more] | MI2016-106 pp.133-136 |
| MI | 2015-07-14 15:40 |
Hokkaido | Sun Refle Hakodate | Semi-automated measurement of mean cerebral blood flow based on dynamic scintigrams Tomohiko Kobota (Gifu Univ), Hiroshi Tago (Japanese Red Cross Gifu Hosp), Takeshi Hara, Daisuke Fukuoka (Gifu Univ), Tetsuro Katafuchi (Gifu Univ of Medical Science), Hiroo Goto (Japanese Red Cross Gifu Hosp), Hiroshi Fujita (Gifu Univ) MI2015-36 |
Patlak plot法は, 脳血流シンチグラフィにおいて低侵襲な平均脳血流量(mCBF)の測定法として利用される. mCBFの値の再現性は認知症の診断に重要である. しかし手動操作による大脳半球, 大動脈弓のROIの設定は、測定値の再現性... [more] | MI2015-36 pp.23-26 |
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