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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI | 2023-03-06 13:41 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Comparative study of the Small Intestine segmentation based on 2D and 3D U-Nets Qin An (Nagoya Univ.), Hirohisa Oda (UoS), SiRui Chen, Yuichiro Hayashi (Nagoya Univ.), Takayuki Kitasaka (Aichi Institute Univ), Hiroo Uchida, Akinari Hinoki (Nagoya Univ.), Kojiro Suzuki (Aichi Medical Univ.), Aitaro Takimoto, Masahiro Oda, Kensaku Mori (Nagoya Univ.)  MI2022-82 |
In this paper, we aim to compare and analyze the small intestine segmentation methods based on U-Net and 3D U-Net. Segme... [more] | MI2022-82 pp.46-51 |
| MI | 2023-03-07 16:50 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Extraction of kidney and renal tumors in a multi-temporal contrast-enhanced CT image database Dai Nishioka, Kento Nishihira, Kaito Koshino, Hidenobu Suzuki, Yoshiki Kawata (Tokushima Univ.), Yuki Kobari (TWMU), Atsushi Ikeda (U. Tsukuba), Noboru Niki (Medical Science Institute Inc.) MI2022-125 |
To develop a highly accurate differentiation method for malignant and benign tumors by precisely analyzing renal and ren... [more] | MI2022-125 pp.210-211 |
| MI | 2023-03-07 17:29 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
High Accuracy Segmentation of trachea and bronchus using 3D U-Net Tatsuya Ogasa, Rikuto Kuroda, Yoshiki Kawata, Hidenobu Suzuki (Tokushima Univ), Yuzi Matsumoto, Takaki Tsuchida, Masahiko Kusumoto (NCC), Noboru Niki (Medical Science Institute Inc.) MI2022-128 |
High-Accuracy trachea and bronchus segmentation is required for lymph node analysis in lung cancer. Since manual segment... [more] | MI2022-128 pp.217-220 |
| EMM | 2023-03-03 11:05 |
Nagasaki | Fukue culture hall (Primary: On-site, Secondary: Online) |
Investigation of Video Watermarking Method Based on 3D U-Net Robust Against Re-shooting Ryota Takahashi (Osaka Prefecture Univ.), Motoi Iwata, Koichi Kise (Osaka Metropolitan Univ.) EMM2022-92 |
In recent years, digital signage has become popular as a device for disseminating information to the masses. However, un... [more] | EMM2022-92 pp.132-137 |
| MI | 2022-09-15 11:25 |
Kanagawa | (Primary: On-site, Secondary: Online) |
Esophageal Tumor Segmentation in Endoscopic Images by Deep Learning Zehao Li, Ken'ichi Morooka (Okayama Univ.), Yuho Ebata (Kyushu Univ.), Hirofumi Hasuda (NHOKMC), Shoko Miyauchi, Ota Mitsuhiko (Kyushu Univ.) MI2022-54 |
Esophageal cancer is often asymptomatic at early stage.It progresses rapidly and can invade surrounding tissues.The esop... [more] | MI2022-54 pp.26-27 |
| MI | 2022-09-15 14:00 |
Kanagawa | (Primary: On-site, Secondary: Online) |
Unsupervised Cell Detection for Suppression of Background Information in Cytology Keita Takeda, Kazuki Matsuo, Kohei Fujiwara, Eiji Mitate, Tomoya Sakai (Nagasaki Univ.) MI2022-57 |
(To be available after the conference date) [more] | MI2022-57 pp.35-38 |
| IN, CCS (Joint) |
2022-08-04 11:10 |
Hokkaido | Hokkaido University(Centennial Hall) (Primary: On-site, Secondary: Online) |
A Study on the Role of Latent Variables in Auto Encoder and U-Net Saki Okamoto, Kenya Jinno (Tokyo City Univ.) CCS2022-29 |
Using U-Net, which introduces Contracting Paths (Concat) into Auto Encoder (AE), we trained the system to output a front... [more] | CCS2022-29 pp.16-19 |
| NS, SR, RCS, SeMI, RCC (Joint) |
2022-07-13 14:50 |
Ishikawa | The Kanazawa Theatre + Online (Primary: On-site, Secondary: Online) |
Investigation of noise removal using U-Net and voice recognition performance improvement
-- for train running noise -- Jian Lin, Shota Sano, Yuusuke Kawakita, Tsuyoshi Miyazaki, Hiroshi Tanaka (KAIT) SeMI2022-26 |
A method for converting noisy sound into images to remove the noise has been proposed. We are attempting to remove train... [more] | SeMI2022-26 pp.34-39 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-20 16:00 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
Application of LambdaNetwork learning long-range interactions between pixels to metal artifact detection Daisuke Shigemori, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) SIP2022-27 BioX2022-27 IE2022-27 MI2022-27 |
Although deep learning-based image transformation has been attempted to be applied to metal artifact reduction, feature ... [more] | SIP2022-27 BioX2022-27 IE2022-27 MI2022-27 pp.138-143 |
| MSS, NLP | 2022-03-29 14:15 |
Online | Online | Weighted Dice Loss for Segmentation from Noisy Labels Toshikazu Samura, Katsumi Tadamura (Yamaguchi Univ.) MSS2021-77 NLP2021-148 |
Deep neural networks (DNNs) are easily affected by noisy labels during training. It degrades the classification performa... [more] | MSS2021-77 NLP2021-148 pp.117-120 |
| CQ, IMQ, MVE, IE (Joint) [detail] |
2022-03-09 11:20 |
Online | Online (Zoom) | Extraction of lung regions from chest CT images using deep learning Xinshan He, Takaharu Yamazaki (SIT) IMQ2021-11 IE2021-73 MVE2021-40 |
Accurate extraction of lung regions from chest X-ray images is an essential process for detecting lesions in lung fields... [more] | IMQ2021-11 IE2021-73 MVE2021-40 pp.7-12 |
| IBISML | 2022-03-09 10:15 |
Online | Online | [Invited Talk]
--- Takahiro Tsukahara (Tokyo University of Science) IBISML2021-41 |
Turbulence of viscoelastic fluids, such as dilute polymer/surfactant solutions, is of practical importance, because it c... [more] | IBISML2021-41 p.34 |
| LOIS | 2022-03-03 16:15 |
Online | Online | A Study on Automatic Segmentation Method for Plant Specimen Images Using U-Net Depeng Zhang, Yasuhiko Higaki, Yasuo Sugai (Chiba Univ.) LOIS2021-47 |
the image processing required to digitize images of plant specimens. Digitized images of plant specimens are very divers... [more] | LOIS2021-47 pp.45-50 |
| MBE, NC (Joint) |
2022-03-04 09:30 |
Online | Online | An estimation method of missing Information of compressed sound source using the Deep U-Net as an Auto-Encoder Kazuma Hirai, Susumu Kuroyanagi (NITech) NC2021-69 |
Some systems of speech-based information transmission, such as radio, telephone, and records, deal with sounds that lack... [more] | NC2021-69 pp.121-126 |
| 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 | 2022-01-25 16:11 |
Online | Online | Uveitis Lesion Detection Using Ultra-Wide Field Fluorescein Angiography Imaging Registration Tomoki Wakitani (Univ. of Shiga Prefecture), Yuji Hatanaka (Oita Univ.), Hiroshi Keino (Kyorin Univ.), Wataru Sunayama (Univ. of Shiga Prefecture) MI2021-49 |
Uveitis is a group of diseases that cause inflammation of the uvea and may lead to blindness. Fluorescein fundus angiogr... [more] | MI2021-49 pp.28-31 |
| SRW, SeMI, CNR (Joint) |
2021-11-26 15:00 |
Tokyo | Kikai-Shinko-Kaikan Bldg. (Primary: On-site, Secondary: Online) |
[Poster Presentation]
A Study on Removal of Train Running Noise using U-Net for Spectrogram Images Motoki Ichikawa, Shota Sano, Jian Lin, Yuusuke Kawakita, Tsuyoshi Miyazaki, Hiroshi Tanaka (KAIT) SRW2021-49 SeMI2021-48 CNR2021-23 |
In this manuscript, we present the results of a study on the effect of speech denoising using spectrogram images obtaine... [more] | SRW2021-49 SeMI2021-48 CNR2021-23 pp.74-78(SRW), pp.61-65(SeMI), pp.51-55(CNR) |
| MI, MICT [detail] | 2021-11-05 11:05 |
Online | Online | [Short Paper]
Description of microvessel structures in 3D reconstructed microscopic pathological images of pancreatic cancer Yuka Ishimaki, Tatsuya Yokota, Kugler Mauricio (NITech), Kenoki Ohuchida (KU), Hidekata Hontani (NITech) MICT2021-33 MI2021-31 |
In this manuscript, we propose a method that segments microvascular regions in a 3D pathological image. For this purpose... [more] | MICT2021-33 MI2021-31 pp.26-27 |
| MI | 2021-07-08 14:00 |
Online | Online | Unsupervised deep learning with low-rank and sparse priors for blood vessel enhancement from free-breathing angiography Ryoji Ishibashi, Tomoya Sakai (Nagasaki Univ.), Hideaki Haneishi (Chiba Univ.) MI2021-11 |
(To be available after the conference date) [more] | MI2021-11 pp.11-14 |
| MI | 2021-03-15 15:30 |
Online | Online | Evaluation of Bayesian Active Learning for Segmentation of Liver and Spleen in Large Scale Abdominal MR Data Sets Bin Zhang, Yoshito Otake, Mazen Soufi (NAIST), Masatoshi Hori (Kobe University), Noriyuki Tomiyama (Osaka University), Yoshinobu Sato (NAIST) MI2020-60 |
Manual annotation in image segmentation is time-consuming and expensive. In order to obtain large number of annotated da... [more] | MI2020-60 pp.62-65 |
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