IEICE Technical Committee

Information and Systems-Image Engineering(Date:2021/03/15)

Presentation

Improvement of deep learning based dementia classification using brain SPECT volumes

Mitsuru Yambe(TUAT), Atsushi Saito(TUAT), Makoto Fukasawa(Fukujuji Hospital), Tomomichi Iizuka(Fukujuji Hospital), Akinobu Shimizu(TUAT),

[Date]2021-03-17
[Paper #]MI2020-86

Report on MICCAI 2020

Atsushi Saito(TUAT), Masahiro Oda(Nagoya Univ.), Yoshito Otake(NAIST), Shouhei Hanaoka(Tokyo Univ.), Ken'ichi Morooka(Okayama Univ.), Shoko Miyauchi(Kyushu Univ.), Yoshitaka Masutani(Hiroshima City Univ.), Chen Shen(Nagoya Univ.), Kensaku Mori(Nagoya Univ.),

[Date]2021-03-17
[Paper #]MI2020-92

Development of marker-less motion correction method for brain dedicated PET system

Yuma Iwao(QST-NIRS), Go Akamatsu(QST-NIRS), Hideaki Tashima(QST-NIRS), Taichi Yamashita(ATOX), Taiga Yamaya(QST-NIRS),

[Date]2021-03-17
[Paper #]MI2020-93

Medical Image Style Translation by Adversarial Training with Paired Inputs

Kazuki Fujioka(Kobe Univ.), Takashi Matsubara(Osaka Univ.), Kuniaki Uehara(Osaka Gakuin Univ.),

[Date]2021-03-17
[Paper #]MI2020-96

Automatic Segmentation of bleeding from Laparoscopic Video using Cascade CNN

Shota Yamamoto(Nagoya Univ.), Yuichiro Hayashi(Nagoya Univ.), Shintaro Morimitsu(Nagoya Univ.), Takayuki Kitasaka(Aichi Institute Tech.), Masahiro Oda(Nagoya Univ.), Nobuyoshi Takeshita(NCC East), Masaaki Ito(NCC East), Kensaku Mori(Nagoya Univ.),

[Date]2021-03-17
[Paper #]MI2020-88

Applications of hybrid reconstruction combining PET and Compton imaging

Hideaki Tashima(NIRS-QST), Eiji Yoshida(NIRS-QST), Takumi Nishina(Chiba Univ.), Sodai Takyu(NIRS-QST), Fumihiko Nishikido(NIRS-QST), Mikio Suga(Chiba Univ.), Hidekatsu Wakizaka(NIRS-QST), Miwako Takahashi(NIRS-QST), Kotaro Nagatsu(NIRS-QST), Atsushi Tsuji(NIRS-QST), Kei Kamada(C&A/Tohoku Univ.), Akira Yoshikawa(C&A/Tohoku Univ.), Katia Parodi(LMU), Taiga Yamaya(NIRS-QST),

[Date]2021-03-17
[Paper #]MI2020-94

Delirium and its indication detection by multiscale CSIs

Yuya Tanaka(Toyohashi Univ. of Tech.), Yuya Hadano(Toyohashi Univ. of Tech.), Yasushi Kanazawa(Toyohashi Univ. of Tech.), Hiroto Sano(NIHON KOHDEN), Wataru Matsuzawa(NIHON KOHDEN), Hideo Oka(Yamaguchi Pref. Grand Medical Center),

[Date]2021-03-17
[Paper #]MI2020-87

Study on automated anatomical labeling of abdominal arteries using Spectral-based Convolutional Graph Neural Networks

Yuta Hibi(Nagoya Univ), Yuichiro Hayashi(Nagoya Univ), Takayuki Kitasaka(Aichi Institute of Tech), Hayato Itoh(Nagoya Univ), Masahiro Oda(Nagoya Univ), Kazunari Misawa(Aichi Cancer Center Hospital), Kensaku Mori(Nagoya University/NII),

[Date]2021-03-17
[Paper #]MI2020-89

Optimal Design and Quality Assessment of Color Laparoscopic Super-Resolution Image by Generative Adversarial Networks

Norifumi Kawabata(Tokyo Univ. of Science), Toshiya Nakaguchi(Chiba Univ.),

[Date]2021-03-17
[Paper #]MI2020-91

[Short Paper] Preliminary study for improving the performance of abdominal multi-phase CT image registration based on 3D deep CNN with a CycleGAN

Ryotaro Fuwa(Gifu Univ.), Xiangong Zhou(Gifu Univ.), Takeshi Hara(Gifu Univ.), Hiroshi Fujita(Gifu Univ.),

[Date]2021-03-17
[Paper #]MI2020-90

Noise reduction method for sparse-view computed tomography using spatial frequency components

Takayuki Okamoto(Chiba Univ.), Hideaki Haneishi(Chiba Univ.),

[Date]2021-03-17
[Paper #]MI2020-95

Using CycleGAN for Metal-induced Streak Artifact Reduction in X-ray CT image

Kazuhiro Nagase(KIT), Yoshihiko Hayakawa(KIT), Pathitta Suteecharuwat(KIT),

[Date]2021-03-17
[Paper #]