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All Technical Committee Conferences (Searched in: Recent 10 Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI | 2025-03-19 13:36 |
Kagawa | Kagawa International Conference Hall (Primary: On-site, Secondary: Online) |
Anomaly Region Detection by Progressive Mask Refinement using Diffusion Models Hiroki Tobise (NIT), Masahiro Hashimoto (Keio Univ.), Toshiaki Akashi (Juntendo Univ.), Hidekata Hontani (NIT)  MI2024-50 |
In this paper, we propose an unsupervised anomaly detection method using a diffusion model. The diffusion model encodes ... [more] | MI2024-50 pp.13-16 |
| MBE, MICT, IEE-MBE [detail] | 2025-01-23 12:30 |
Fukuoka | Kyushu Institute of Technology | Analysis of Response of Large Language Model to the Difficult Medical Engineering Examinations Kai Ishida (SIT) MICT2024-54 MBE2024-35 |
Recently, large language models (LLM) have quickly gained popularity in medical applications. It has been reported that ... [more] | MICT2024-54 MBE2024-35 pp.30-33 |
| PRMU, IPSJ-CVIM, VRSJ-SIG-MR, MVE | 2025-01-21 13:35 |
Fukuoka | (Primary: On-site, Secondary: Online) |
Anomaly Region Detection in Medical Images using Diffusion Models with Simplex Noise and Progressive Mask Refinement Hiroki Tobise (NIT), Masahiro Hashimoto (Keio Univ.), Toshiaki Akashi (Juntendo Univ.), Hidekata Hontani (NIT) PRMU2024-36 |
In this paper, we propose an anomaly detection method that uses a diffusion model as an autoencoder. The diffusion model... [more] | PRMU2024-36 pp.18-23 |
| MICT, MI | 2024-12-05 10:20 |
Osaka | Jikei University of Health Care Sciences | Fine-Tuning LLaVA-Med 1.5 for Automated Biomedical Report Generation on MRI Scans Ahmed Tamer ELBoardy, Nouman Muhammad, Essam A. Rashed (UH) MICT2024-32 MI2024-30 |
This study explores the use ofLLaVA-Med1.5,a specialized large language and vision model tailored for biomedicine, ... [more] |
MICT2024-32 MI2024-30 pp.17-19 |
| MICT, MI | 2024-12-05 17:00 |
Osaka | Jikei University of Health Care Sciences | Evaluating MedSAM: Addressing Clinical Performance and Segmentation Challenges Muhammed Nouman, Ahmed Tamer ELBoardy (UH), Ghada Khoriba (NU), Essam A. Rashed (UH) MICT2024-48 MI2024-46 |
[more] | MICT2024-48 MI2024-46 pp.78-79 |
| 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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| 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 |
| MBE, IEE-MBE | 2023-06-16 14:10 |
Hokkaido | Hokkaido University (Primary: On-site, Secondary: Online) |
Development of an Extra-corporeal circuit Assembly Support System Using Image Recognition Hisashi Miyazaki (Nippon Bunri Univ.), Takayuki Torigoe, Isao Kayano (Kawasaki Univ. of Medical Welfare) MBE2023-9 |
In this research, we developed a system that automatically displays an assembly manual for an artificial heart-lung mach... [more] | MBE2023-9 p.3 |
| SC | 2023-06-03 10:35 |
Fukushima | UBIC 3D Theater, University of Aizu (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Understanding transfer learning for medical image classification. Dao Ngoc HOng, Paik Incheon (UoA) SC2023-9 |
Transfer learning is one of the critical solutions to deal with the problem of data scarcity, where the learning process... [more] | SC2023-9 pp.48-52 |
| CCS | 2023-03-27 09:00 |
Hokkaido | RUSUTSU RESORT | Medical Image Segmentation with Inverse Heat Dissipation Model Yu Kashihara, Takashi Matsubara (Osaka Univ.) CCS2022-82 |
The diffusion model is a generative model based on stochastic transitions and has been successfully used to generate an... [more] |
CCS2022-82 pp.107-112 |
| 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 |
| MBE, MICT, IEE-MBE [detail] | 2023-01-17 10:40 |
Saga | Potential problems that will arise for hospital LANs Eisuke Hanada (Saga Univ.), Takato Kudou (Oita Univ.) MICT2022-46 MBE2022-46 |
Hospital Information Systems (HIS) have been introduced in almost all large hospitals. In addition to this, IP networks ... [more] | MICT2022-46 MBE2022-46 pp.17-21 |
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| IMQ | 2022-12-16 15:30 |
Chiba | Nishi-Chiba Campus, Chiba Univ. | A Study of Correction Method for Calculation Error of Auscultation Position in Augmented Reality Type Auscultation Training Simulator Yoshito Mikado, keiichiro miura, Hajime Kasai, Shoichi Ito, Asahina Mayumi, Masahiro Tanabe, Yukihiro Nomura, Toshiya Nakaguchi (Chiba Univ.) IMQ2022-17 |
Current auscultation training for healthcare professionals is conducted using a simulated patient and a mannequin for au... [more] | IMQ2022-17 pp.12-15 |
| MI | 2022-07-08 17:00 |
Hokkaido | (Primary: On-site, Secondary: Online) |
[Short Paper]
Weakly-Supervised Focal Liver Lesion Detection in CT Images He Li, Yutaro Iwamoto (Ritsumeikan Univ.), Xianhua Han (Yamaguchi Univ.), Lanfen Lin, Ruofeng Tong, Hongjie Hu (Zhejiang Univ.), Akira Furukawa (Tokyo Metropolitan Univ.), Shuzo Kanasaki (Koseikai Takeda Hospital), Yen-Wei Chen (Ritsumeikan Univ.) MI2022-40 |
Convolutional neural networks have been widely used for anomaly detection and one of their most common methods is autoen... [more] | MI2022-40 pp.30-33 |
| 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 |
| 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 |
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