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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SIS, IPSJ-AVM [detail] | 2023-06-15 11:10 |
Shimane | NIT, Matsue College (Primary: On-site, Secondary: Online) |
A New Detection Method of Calcification Regions in Dental Panoramic Radiograph and Application of MTL in Its Learning Taito Murano, Mitsuji Muneyasu, Soh Yoshida, Akira Asano (Kansai Univ.), Keiichi Uchida (Matsumoto Dental Univ. Hospital,)  SIS2023-2 |
Calcification regions, considered a sign of atherosclerosis, are sometimes observed in the carotid arteries in dental pa... [more] | SIS2023-2 pp.7-12 |
| SIS, IPSJ-AVM [detail] | 2023-06-15 11:35 |
Shimane | NIT, Matsue College (Primary: On-site, Secondary: Online) |
Detection of Calcification Regions from Dental Panoramic Radiograph Based on Semantic Segmentation Using Transformers Taito Murano, Mitsuji Muneyasu, Soh Yoshida, Akira Asano (Kansai Univ.), Keiichi Uchida (Matsumoto Dental Univ. Hospital,) SIS2023-3 |
Calcification regions, considered a sign of atherosclerosis, are sometimes observed in the carotid arteries in dental pa... [more] | SIS2023-3 pp.13-18 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 09:30 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Detection of UI parts from web page images utilizing a small amount of data Wataru Aizaki, Sotaro Kato, Yoshihisa Shinozawa (Keio Univ.), Yukako Iimura, Shinobu Saito (NTT) PRMU2022-61 IBISML2022-68 |
The purpose of our research is to devise a method for detecting UI parts in a Web screen. The proposed method consists o... [more] | PRMU2022-61 IBISML2022-68 pp.17-22 |
| MI | 2021-08-27 15:00 |
Online | Online | [Short Paper]
Region extraction and mass estimation of kidneys from Ai-CT Yasushi Hirano, Remi Yamashita (Yamaguchi Univ.), Shoji Kido (Osaka Univ.), Kunihiro Inai (Univ. of Fukui) MI2021-24 |
Autopsy imaging (Ai) is an examination method for investigating the cause of death and estimating the postmortem time. S... [more] | MI2021-24 pp.10-11 |
| SIS | 2021-03-04 13:30 |
Online | Online | Improvement of Detection Accuracy of Calcification Regions from Dental Panoramic Radiograph Using Deep Learning Taito Murano, Mitsuji Muneyasu, Soh Yoshida, Akira Asano (Kansai Univ.), Keiichi Uchida (Matsumoto Dental Univ. Hospital), Dewake Nanae, Yasuaki Ishioka, Nobuo Yoshinari (Matsumoto Dental Univ.) SIS2020-45 |
Dental panoramic radiographs may show calcified areas that are a sign of vascular disease. Finding these areas in dentis... [more] | SIS2020-45 pp.55-60 |
| MI | 2020-09-03 10:00 |
Online | Online | Lung region segmentation of thoracoscopic image with unsupervised image translation Jumpei Nitta, Megumi Nakao (Kyoto Univ.), Keiho Imanishi (e-Growth Co. Ltd.), Tetsuya Matsuda (Kyoto Univ.) MI2020-19 |
In endoscopic surgery, it is necessary to understand the three-dimensional structure of the target region to improve saf... [more] | MI2020-19 pp.13-18 |
| ITE-HI, IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2020-02-27 16:35 |
Hokkaido | Hokkaido Univ. (Cancelled but technical report was issued) |
A Study on Region Segmentation of Color Laparoscopic Images after Contrast Enhancement Including Super-Resolution CNN by Image Regions Norifumi Kawabata (Tokyo Univ. of Science), Toshiya Nakaguchi (Chiba Univ.) |
As one of image pre-processing method to detect, recognize, and estimate lesion or characteristic region in medical imag... [more] | |
| MI | 2020-01-30 13:25 |
Okinawa | OKINAWAKEN SEINENKAIKAN | 2D Deep CNN for automated multi organ segmentation from CT images by using consecutive slices feature maps Hiroki Isakari, Xiangrong Zhou, Takeshi Hara, Hiroshi Fujita (Gifu Univ.) MI2019-113 |
The development of a computer-aided diagnosis system is expected to reduce the burden on the radiologist in clinical pra... [more] | MI2019-113 pp.203-205 |
| MVE | 2019-08-29 11:20 |
Aichi | Severity Index Evaluation using Automatic Region of Interest Segmentation Patinya Tantawiwat, Datchakorn Tancharoen (PIM), Toshihiko Yamasaki (UTokyo) MVE2019-5 |
Psoriasis Area and Severity Index (PASI) is currently a standard approach to quantify severity of psoriasis. In this pap... [more] | MVE2019-5 pp.13-16 |
|
| MI | 2019-07-06 11:55 |
Hokkaido | Future Univ. Hakodate | [Poster Presentation]
Basic study of left atrial appendage segmentation from cardiac CT images Itaru Takayashiki, Doi Akio, Toru Kato, Hiroki Takahashi (Iwate Prefectural Univ.), Shoto Sekimura (ISP), Maiko Hozawa, Yoshihiro Morino (Iwate Medical Univ.) MI2019-30 |
In this study, we propose a method to automatically extract the left atrial appendage region from the cardiac CT image f... [more] | MI2019-30 pp.43-48 |
| 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] | |
| AI | 2018-12-07 16:20 |
Fukuoka | Proposal of Method for Detecting White-of-Eye Region in Grayscale Character Line Drawing for Automatic Colorization Masashi Aizawa, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga (UEC) AI2018-31 |
Colorizing line drawings requires special skill, experience, knowledge. And artists consume a lot of time and effort in ... [more] | AI2018-31 pp.31-35 |
|
| CS, IE, IPSJ-AVM, ITE-BCT [detail] | 2018-11-30 14:50 |
Tokushima | Tokushima University (Memorial Hall of Almuni(Engineering)) | Classification of man-made objects and nature-made objects in images using independent component analysis and orientation map Yukihiro Dozono, Yukinori Suzuki (Muroran IT) CS2018-85 IE2018-64 |
Classification of man-made objects and nature-made objects is an essential task in region segmentation of natural images... [more] | CS2018-85 IE2018-64 pp.111-116 |
| CAS, SIP, MSS, VLD | 2018-06-14 14:50 |
Hokkaido | Hokkaido Univ. (Frontier Research in Applied Sciences Build.) | Image Haze Reduction Method by Ambient Light Estimation Using Region Segmentation Yuji Araki, Koichi Ichige (Yokohama National Univ.) CAS2018-10 VLD2018-13 SIP2018-30 MSS2018-10 |
In this paper, we propose an accurate haze reduction method that divides hazed images into regions in advance, where haz... [more] | CAS2018-10 VLD2018-13 SIP2018-30 MSS2018-10 pp.51-56 |
| IE, ITE-ME, ITE-AIT [detail] | 2017-10-05 14:50 |
Nagasaki | Segmentation of Campus Images based on Image Features for Building Recognition Kenta Yamanishi, Shun Hattori, Yukinori Suzuki (Muroran-IT) IE2017-51 |
We have been studying building recognition in natural images by taking picture in a college campus. Itis difficult to re... [more] | IE2017-51 pp.25-30 |
|
| PRMU, BioX | 2017-03-21 10:00 |
Aichi | [Short Paper]
Bile duct segmentation from 3D CT image based on machine learning and probability map-assisted region growing Pengfei Chen, Hiroshi Tanaka, Masahiro Oda, Holger Roth, Tsuyoshi Igami, Masato Nagino, Kensaku Mori (NU) BioX2016-55 PRMU2016-218 |
In this paper, we present our study on the bile duct segmentation from 3D CT volumes. In hepatobiliary surgery, it is re... [more] | BioX2016-55 PRMU2016-218 pp.135-136 |
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| PRMU, IE, MI, SIP | 2016-05-19 13:30 |
Aichi | Automatic classification of breast density on CT images by using deep CNN Takuya Kano, Xiangrong Zhou (Gifu Univ.), Hiromi Koyasu (Gifu Univ. Hosp.), Ryuziro Yokoyama, Takeshi Hara (Gifu Univ.), Masayuki Matsuo (Gifu Univ. Hosp.), Hiroshi Fujita (Gifu Univ.) SIP2016-5 IE2016-5 PRMU2016-5 MI2016-5 |
Breast density has been used as an important risk factor of breast cancer and routinely measured on 2D mammography. 3D C... [more] | SIP2016-5 IE2016-5 PRMU2016-5 MI2016-5 pp.21-25 |
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| MI | 2016-01-19 13:20 |
Okinawa | Bunka Tenbusu Kan | An automatic segmentation of the pelvic MRI for the PET attenuation correction Hiroshi Kawaguchi (AIST), Takayuki Obata, Hiromi Sano, Eiji Yoshida (NIRS), Mikio Suga (Chiba Univ.), Yoko Ikoma (NIRS), Yukari Tanikawa (AIST), Taiga Yamaya (NIRS) MI2015-82 |
The automatic segmentation method of the MR image is mandatory to construct attenuation correction data for the clinical... [more] | MI2015-82 pp.51-54 |
| SIS | 2015-12-03 16:00 |
Fukui | Matsuya-sensen (Awara city, Fukui) | Analysis Aiding System for Cell Image Sequences Kohei Watarai, Yutaka Nakano, Toshiyuki Yoshida (Fukui Univ) SIS2015-36 |
In some biological areas, an analysis aiding system is required that realizes an automatic cell-region segmentation and ... [more] | SIS2015-36 pp.41-45 |
| MI | 2015-03-03 13:40 |
Okinawa | Hotel Miyahira | Generation of attenuation correction factor for PET from a T1-weighted pelvic MR image using hybrid-segmentation and atlas method Hiroshi Kawaguchi, Takayuki Obata, Hiromi Sano, Eiji Yoshida (NIRS), Mikio Suga (Chiba Univ.), Yoko Ikoma, Taiga Yamaya (NIRS) MI2014-99 |
The current attenuation correction method for human pelvic PET/MRI contains several problems such that the attenuation d... [more] | MI2014-99 pp.221-226 |
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