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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI, MICT | 2023-11-14 13:20 |
Fukuoka | Medical image diagnosis support system with image anonymization based on deep learning techniques Katsuto Iwai, Ryuunosuke Kounosu (Toho Univ./AIST), Hirokazu Nosato (AIST), Yuu Nakajima (Toho Univ.)  MICT2023-30 MI2023-23 |
When medical imaging AI models are hosted on cloud service there is a risk of sensitive medical images being leaked when... [more] | MICT2023-30 MI2023-23 pp.21-24 |
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| 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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| 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 | 2022-01-26 13:00 |
Online | Online | Relationship between Image Quality and Learning Effect in Color Laparoscopic Images Generation by Generative Adversarial Networks Norifumi Kawabata (Hokkaido Univ.), Toshiya Nakaguchi (Chiba Univ.) MI2021-59 |
Improving of personal computer performance, it is possible for healthcare workers and related researchers to support for... [more] | MI2021-59 pp.59-64 |
| 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 |
| IBISML | 2022-01-18 11:15 |
Online | Online | [Invited Talk]
TBA Jun Sakuma (Tsukuba Univ./RIKEN) |
Explainability is one of the key elements required in medical image diagnosis using deep image recognition models. In th... [more] | |
| CCS | 2021-11-19 14:30 |
Osaka | Osaka Univ. (Primary: On-site, Secondary: Online) |
A Study of Deep Learning for Abnormal Waveforms in ECG Image Data Using Expert Diagnosis as a Teacher Kentaro Hashimoto, Yuichiro Yamamura (Univ of Tsukuba.), Ryota Iwatsuka (Taiyo-kai Social Welfare awachiiki iryo center), Hiroyasu Ando (Tohoku Univ./Univ of Tsukuba.) CCS2021-33 |
Artificial intelligence is expected to play a variety of roles in the medical fields. Diagnosis based on ECG readings is... [more] | CCS2021-33 pp.89-93 |
| MI | 2021-03-17 11:00 |
Online | Online | Optimal Design and Quality Assessment of Color Laparoscopic Super-Resolution Image by Generative Adversarial Networks Norifumi Kawabata (Tokyo Univ. of Science), Toshiya Nakaguchi (Chiba Univ.) MI2020-91 |
The Generative Adversarial Networks (GAN) is unsupervised learning enabled to transform according to data characteristic... [more] | MI2020-91 pp.186-190 |
| IMQ | 2020-10-02 15:20 |
Online | Online | Development of software simulator for display design of 3D volumetric display Du Leran (Chiba Univ.), Ryutaro Okamoto (Teidec), Shinsuke Akita, Yuichiro Yoshimura, Toshiya Nakaguchi (Chiba Univ.) IMQ2020-6 |
Intuitive understanding of the human body structure in three dimensions is important for diagnosis, treatment, informed ... [more] | IMQ2020-6 pp.9-12 |
| 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] | |
| VLD, DC, CPSY, RECONF, CPM, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC (Joint) [detail] |
2018-12-07 12:30 |
Hiroshima | Satellite Campus Hiroshima | [Keynote Address]
AI in medical imaging diagnosis Hiroshi Fujita (Gifu Univ.) VLD2018-68 CPM2018-93 ICD2018-54 IE2018-72 CPSY2018-39 DC2018-54 RECONF2018-45 |
It is entering the third artificial intelligence (AI) boom. In particular, with the advent of "deep learning" technology... [more] | VLD2018-68 CPM2018-93 ICD2018-54 IE2018-72 CPSY2018-39 DC2018-54 RECONF2018-45 p.201(VLD), p.27(CPM), p.27(ICD), p.27(IE), p.31(CPSY), p.201(DC), p.61(RECONF) |
| 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 |
| SIP | 2016-08-25 15:30 |
Chiba | Chiba Institute of Technology, Tsudanuma Campus | [Invited Talk]
Applications of Deep learning for image diagnosis Hayaru Shouno (UEC) SIP2016-76 |
The ``deep learning'' is the 3rd generation neural network technology, which is exhibiting its characteristics in the bi... [more] | SIP2016-76 pp.23-24 |
| MI | 2015-03-02 13:40 |
Okinawa | Hotel Miyahira | Semi-automatic region detection of maxillary sinus on dental panoramic radiograph Yuma Miki, Takeshi Hara, Chisako Muramatsu (Gifu Univ.), Tatsuro Hayashi (Media), Akitoshi Katsumata (Asahi Univ.), Xiangrong Zhou, Hiroshi Fujita (Gifu Univ.) MI2014-77 |
Recently, a diagnosis using a dental panoramic radiograph is frequently performed. We previously developed a method to d... [more] | MI2014-77 pp.111-114 |
| IE, ITE-AIT, ITE-ME [detail] | 2014-11-07 10:00 |
Kagoshima | A study on improvement of microcalcification attenuation in medical image denoising using NL-means Tsuyoshi Yamashita (Kanazawa Univ.), Mamoru Ogaki (EIZO Co.), Marina Katou, Kousuke Imamura, Yoshio Matsuda, Shigeru Sanada (Kanazawa Univ.) IE2014-57 |
Image processing technology in medical field is attracting attention as a solution to realize improvement of diagnosis a... [more] | IE2014-57 pp.45-50 |
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| MI | 2014-06-24 14:15 |
Fukuoka | Lecture Hall, Building B of Basic Sciences, Kyushu University | [Special Talk]
[Special Talk] Introduction of Development of Korean Biopsy Robot Joon Beom Seo, Namkug Kim, Jaesoon Choi (AMC, Univ. of Ulsan) MI2014-33 |
Needle insertion or puncturing is one of most common procedures for both diagnosis and treatment of various diseases in ... [more] | MI2014-33 pp.59-61 |
| IBISML | 2013-07-18 15:40 |
Tokyo | Nishiwaseda Campus (Waseda univ.) | Computer aided image diagnosis system using artificial intelligence for X-ray CT image Tadashi Kondo, Junji Ueno, Shoichiro Takao (Tokushima Univ.) IBISML2013-11 |
A computer aided image diagnosis system using artificial intelligence for X-ray CT image is developed. In this system, a... [more] | IBISML2013-11 pp.75-80 |
| MI | 2013-07-19 10:00 |
Miyagi | A Study of a High-Accuracy Ultrasound Contrast Agent Detection Method for Diagnostic Ultrasound Imaging Systems Koichi Ito, Kazumasa Noro, Yukari Yanagisawa, Maya Sakamoto, Shiro Mori (Tohoku Univ.), Kiyoto Shiga (Iwate Medical Univ.), Tetsuya Kodama, Takafumi Aoki (Tohoku Univ.) MI2013-31 |
This paper presents a high-accuracy microbubble detection method for diagnostic ultrasound imaging systems. The conventi... [more] | MI2013-31 pp.61-65 |
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| IE | 2013-04-26 16:15 |
Tokyo | Chuo Univ. | Multi-layered GMDH-type neural network using Predicton Sum of Square (PSS) and its application to medical image diagnosis of liver cancer Tadashi Kondo, Junji Ueno, Shoichiro Takao (Tokushima Univ.) IE2013-7 |
(To be available after the conference date) [more] | IE2013-7 pp.35-40 |
| PRMU, IBISML, IPSJ-CVIM (Joint) [detail] |
2012-09-02 11:00 |
Tokyo | Medical image diagnosis of liver cancer by revised GMDH-type neural network self-organizing neural network architectures using heuristic self-organization Tadashi Kondo, Junji Ueno, Shoichiro Takao (Tokushima Univ.) PRMU2012-32 IBISML2012-15 |
In this study, a feedback Group Method of Data Handling (GMDH)-type neural network self-organizing neural network archit... [more] | PRMU2012-32 IBISML2012-15 pp.17-22 |
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