Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
MI |
2024-03-03 09:41 |
Okinawa |
OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
A preliminary study on deep causal discovery model for image classification Ryohei Motoda, Megumi Nakao (Kyoto Univ.) MI2023-33 |
Although saliency map used in image classification can visualize the regions correlated with predicted class, it cannot ... [more] |
MI2023-33 pp.11-14 |
MI |
2024-03-03 14:00 |
Okinawa |
OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Invited Lecture]
Latest Research Trends 2023: Image Segmentation and General Overview of MICCAI Masahiro Oda (Nagoya Univ.), Itaru Otomaru (Canon), Ryo Furukawa (Kindai Univ.), Kensaku Mori (Nagoya Univ.) MI2023-46 |
In this paper, we overview the outlines of MICCAI 2023's main conference sessions and satellite workshops. Several inter... [more] |
MI2023-46 pp.45-49 |
MI |
2024-03-04 10:46 |
Okinawa |
OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Automated musculoskeletal segmentation of torso CT images Sanaa Amina Gourine, Mazen Soufi, Yoshito Otake (NAIST), Yuto Masaki (NAIST-PSP Corporation), Yoko Murakami, Yukihiro Nagatani, Yoshiyuki Watanabe (Shiga Univ), Keisuke Uemura (Osaka Univ), Masaki Takao (Ehime Univ), Nobuhiko Sugano (Osaka Univ), Yoshinobu Sato (NAIST) MI2023-70 |
Musculoskeletal segmentation (MSK) in CT is helpful for several applications, including body composition analysis, biome... [more] |
MI2023-70 pp.122-126 |
MI |
2024-03-04 11:10 |
Okinawa |
OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Identification of follicle segmentation and subtype in a lymph node HE-stained image based on the set of cell nuclei Mizuki Moribe, Tatsuya Yokota (NIT), Koichi Oshima, Hiroaki Miyoshi, Miharu Nagaishi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (NU), Hidekata Hontani (NIT) MI2023-72 |
In this paper, we report on a method for follicle segmentation and the identification of malignant lymphoma subtypes usi... [more] |
MI2023-72 pp.131-132 |
MI |
2024-03-04 12:52 |
Okinawa |
OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Uncertainty-Boosted COVID-19 Lesion Segmentation Method from Chest CT Images Tianyu Yang, Masahiro Oda, Tong Zheng, Yuichiro Hayashi, Kensaku Mori (Nagoya Univ) MI2023-74 |
The spread of COVID-19 pandemic has severely threatened global health in recent years. Deep learning based method for CO... [more] |
MI2023-74 pp.137-140 |
MI |
2024-03-04 13:04 |
Okinawa |
OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Extraction of phalanges regions from hand CT images using 3D U-Net Madoka Okada, Takaharu Yamazaki, Yusei Arisawa (SIT), Kazuaki Tanaka (Neomedical), Keizo Fukumoto (Saitama Jikei) MI2023-75 |
Accurate extraction of phalanges regions from hand CT images is important to support accurate image diagnosis, treatment... [more] |
MI2023-75 pp.141-144 |
MI |
2023-09-08 11:20 |
Osaka |
(Primary: On-site, Secondary: Online) |
A Study on Identifying Gender Differences Using Deep Learning from Retinal Fundus Images Shota Tsutsui (Waseda Univ.), Ichiro Maruko, Moeko Kawai (TWMU), Yoichi Kato, Jun Ohya (Waseda Univ.) MI2023-17 |
Previous studies show that a properly designed and trained deep learning algorithm is capable to identify the gender of ... [more] |
MI2023-17 pp.8-11 |
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 |
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 |
IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-16 14:25 |
Okinawa |
Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
Pear flower pollination path estimation using deep learning and combinatorial optimization Keita Endo (NIT), Tomotaka Kimura (Doshisha Univ.), Hiroyuki Shimizu (NIT), Tomohito Shimada, Akane Shibasaki (SATRC), Yoshihiro Takemura (Tottori Univ.), Takefumi Hiraguri (NIT) CQ2022-95 |
Since fruit trees are grown outdoors, they require heavy and long hours working. In among fruit trees, pears needs artif... [more] |
CQ2022-95 pp.74-77 |
IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-17 15:40 |
Okinawa |
Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
Improvement of cross-attention modules for image captioning using pixel-wise semantic information Zhihao Chen, Keisuke Doman, Yoshito Mekada (Chukyo Univ.) IMQ2022-84 IE2022-161 MVE2022-114 |
Most of image captioning models have attention modules, and the module outputs an attention map (weighted feature map) f... [more] |
IMQ2022-84 IE2022-161 MVE2022-114 pp.333-338 |
MI |
2023-03-06 13:15 |
Okinawa |
OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Improvement of Small Organ Accuracy in Multi-Organ Segmentation of Abdominal CT Images Using 2.5D Deformable Convolutional CNN Yuya Okumura, Hiroyuki Kudo, Hotaka Takizawa (Univ of Tsukuba) MI2022-80 |
In multi-organ segmentation of abdominal CT images using deep learning, small organs such as the pancreas are difficult ... [more] |
MI2022-80 pp.38-39 |
MI |
2023-03-06 16:00 |
Okinawa |
OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Segmentation of renal cancers from multi-phase CT images by deep learning using selective fusion Masanobu Gido (Tsukuba Univ.), Ryo Tanimoto, Kensaku Mori, Hideki Kakeya (Tsukuba Univ.) MI2022-92 |
Multiphase CT images are commonly used for the diagnosis of renal cancer. In this paper, we propose a machine learning s... [more] |
MI2022-92 pp.94-99 |
PRMU |
2022-12-15 10:45 |
Toyama |
Toyama International Conference Center (Primary: On-site, Secondary: Online) |
DN4C
-- An Interactive Image Segmentation System Combining Deep Neural Network and Nearest Neighbor Classifier -- Toshikazu Wada, Koji Kamma (Wakayama University) PRMU2022-35 |
Color/texture based image segmentation can be widely applied to the images for product and/or medical inspection, remote... [more] |
PRMU2022-35 pp.19-24 |
RCC, ITS, WBS |
2022-12-14 10:40 |
Shiga |
Ritsumeikan Univ. BKC (Primary: On-site, Secondary: Online) |
A Study on Identification of Bicycle Riding Environment by Image Segmentation and Transfer Learning Hiroaki Arai, Tetsuya Manabe (Saitama Univ.) WBS2022-54 ITS2022-30 RCC2022-54 |
This paper examines the identification of the bicycle riding environment by image segmentation and transfer learning. W... [more] |
WBS2022-54 ITS2022-30 RCC2022-54 pp.108-113 |
SIS |
2022-12-05 14:50 |
Osaka |
(Primary: On-site, Secondary: Online) |
A Method of Automatic Wall Detection from Room Images by Deep Neural Networks Shunya Shimegi, Kaoru Arakawa (Meiji Univ.) SIS2022-27 |
In order to design interior renovation easily,a method of automatic wall area detection is proposed using deep neural ne... [more] |
SIS2022-27 pp.21-25 |
MIKA (3rd) |
2022-10-13 11:10 |
Niigata |
Niigata Citizens Plaza (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Route optimization for pear flower pollination using segmentation method Keita Endo (NIT), Tomotaka Kimura (Doshisha Univ.), Hiroyuki Shimizu (NIT), Tomohito Shimada (SATRC), Yoshihiro Takemura (Tottori Univ.), Takefumi Hiraguri (NIT) |
Fruit cultivation is less mechanized than vegetable cultivation and requires manual labor. Therefore, it requires long l... [more] |
|
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 |
PRMU |
2022-09-14 16:15 |
Kanagawa |
(Primary: On-site, Secondary: Online) |
Data Augmentation with Style Transfer for Fossil Image Segmentation Akihiro Waza (Osaka Metropolitan Univ.), Yuya Inamura (Osaka Prefecture Univ.), Katsufumi Inoue, Michifumi Yoshioka, Toshihiro Yamada (Osaka Metropolitan Univ.) PRMU2022-17 |
Fossils are extremely important materials in evolutionary biology and earth science. However, it is necessary to have sp... [more] |
PRMU2022-17 pp.43-48 |
CS |
2022-07-14 12:00 |
Kagoshima |
Yakushima Environmental and Cultural Village Center (Primary: On-site, Secondary: Online) |
Studys on pollination route estimation method for flowers of pear using field images Keita Endo (NIT), Tomotaka Kimura (Doshisha Univ.), Hiroyuki Shimizu (NIT), Yoshihiro Takemura (Tottori Univ.), Takefumi Hiraguri (NIT) CS2022-19 |
Fruit cultivation requires hand and long working compared with vegetable cultivation because careful cares greatly affec... [more] |
CS2022-19 pp.34-35 |