Online edition: ISSN 2432-6380
[TOP] | [2016] | [2017] | [2018] | [2019] | [2020] | [2021] | [2022] | [Japanese] / [English]
PRMU2019-12
(See Japanese page.)
pp. 3 - 7
PRMU2019-13
(See Japanese page.)
pp. 9 - 13
PRMU2019-14
[Short Paper]
Quantitative evaluation of lymph nodes in colorectal cancer using 3-phase abdominal CT images
Ren Nishimoto, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki (Tokushima Univ.), Gen Iinuma (NCC)
pp. 15 - 18
PRMU2019-15
Domain-adversarial multiple instance learning for subtype classification of malignant lymphoma
Daisuke Fukushima, Ryoichi Koga, Noriaki Hashimoto, Kaho Ko (Nagoya Inst. of Tech), Masato Nakaguro, Kei Kohno, Shigeo Nakamura (Nagoya Univ. Hospital), Hidekata Hontani (Nagoya Inst of Tech), Ichiro Takeuchi (Nagoya Inst. of Tech/RIKEN/NIMS)
pp. 19 - 24
PRMU2019-16
Preliminary investigation on decomposition of individual muscles and bones of lower extremity from single radiograph using CycleGAN
Naoki Nakanishi, Yuta Hiasa, Yoshito Otake (NAIST), Masaki Takao, Nobuhiko Sugano (Osaka Univ.), Yoshinobu Sato (NAIST)
pp. 25 - 30
PRMU2019-17
Analysis of pneumothorax deformation for in vivo animal lungs using model-based registration
Kotaro Kobayashi, Megumi Nakao (Kyoto Univ.), Junko Tokuno, Toyofumi F. Chen-Yoshikawa, Hiroshi Date (Kyoto Univ. Hospital), Tetsuya Matsuda (Kyoto Univ.)
pp. 31 - 36
PRMU2019-18
(See Japanese page.)
pp. 37 - 42
PRMU2019-19
Inter-frame interpolation by height constraint for sequential human silhouette images
-- Application to forensic gait analysis under low frame-rate condition --
Daisuke Imoto, Kenji Kurosawa, Masakatsu Honma, Ryo Yokota, Manato Hirabayashi, Yoshinori Hawai (NRIPS)
pp. 43 - 48
PRMU2019-20
(See Japanese page.)
pp. 49 - 52
PRMU2019-21
[Short Paper]
Soft-constrained clustering for facilitating image labeling
Ryoma Bise, Kentaro Abe, Hideaki Hayashi (Kyushu Univ.), Kiyohito Tanaka (Kyoto Second Red Cross Hospital), Seiichi Uchida (Kyushu Univ.)
pp. 53 - 56
PRMU2019-22
(See Japanese page.)
pp. 57 - 61
PRMU2019-23
Metal artifact reduction using CycleGAN for CT images
Megumi Nakao (Kyoto Univ.), Kieho Imanishi (e-Grwoth), Nobuhiro Ueda (Nara Med.), Yuichiro Imai (Otowa Hosp.), Tadaaki Kirita (Nara Med.), Tetsuya Matsuda (Kyoto Univ.)
pp. 63 - 68
PRMU2019-24
[Short Paper]
Dynamic PET Image Reconstruction using Non-Negative Matrix Decomposition with Deep Image Prior
Tomoshige Shimomura, Kazuya Kawai (NIT), Muneyuki Sakata (Tokyo Metro. Inst. Gerontology), Yuichi Kimura (KU), Tatsuya Yokota, Hidekata Hontani (NIT)
pp. 69 - 70
PRMU2019-25
A method for visualizing the cause of misrecognition in object recognition using CNN
Tomonori Kubota (Fujitsu Lab.), Yasuyuki Murata (FST), Yoshifumi Uehara, Akira Nakagawa (Fujitsu Lab.)
pp. 99 - 104
PRMU2019-26
Hierarchical Classification to Detect Type of Diseases and Abnormality Simultaneously in Optical Coherence Tomography Images
Yudai Kato, Yuji Ayatsuka, Takaki Uta (CRESCO), Soichiro Kuwayama, Hideaki Usui, Aki Kato, Yuichiro Ogura, Tsutomu Yasukawa (Nagoya City University)
pp. 105 - 108
PRMU2019-27
Rough domain adaptation through model selection for neural networks
Azusa Sawada, Takashi Shibata, Shoji Yachida (NEC)
pp. 109 - 113
PRMU2019-28
Active learning based on self-supervised feature learning
Shunsuke Tsukatani, Kazuhiko Murasaki, Shingo Andou, jun Shimamura (NTT)
pp. 115 - 119
PRMU2019-29
Analysis and Feature Selection of CNN Features
-- Recognition of Neoplasia by using Endocytoscopic Images --
Hayato Itoh (Nagoya Univ.), Yuichi Mori, Masashi Misawa (Showa Univ.), Masahiro Oda (Nagoya Univ.), Shin-Ei Kudo (Showa Univ.), Kensaku Mori (Nagoya Univ.)
pp. 129 - 134
PRMU2019-30
Mixed Domain Learning for Computer-aided Diagnosis of Endoscopy Images in Deep Convolutional Neural Networks
Yuta Kochi (Tsukuba Univ./AIST), Hirokazu Nosato, Masahiro Murakawa, Hidenori Sakanashi (AIST)
pp. 135 - 138
Note: Each article is a technical report without peer review, and its polished version will be published elsewhere.