Paper Abstract and Keywords |
Presentation |
2020-09-03 09:30
Segmentation of Layer Structure of Stomach Wall and Tumor from MicroCT volumes Using Neural Network and Spherical K-means Midori Mitarai, Hirohisa Oda, Takaaki Sugino, Takayasu Moriya, Hayato Itoh, Masahiro Oda, Takuma Komiyama, Kazuhiro Furukawa, Ryoji Miyahara, Mitsuhiro Fujishiro (Nagoya Univ.), Masaki Mori (Sapporo-Kosei General Hospital), Hirotsugu Takabatake (Sapporo Minami-sanjo Hospital), Hiroshi Natori (Keiwakai Nishioka Hospital), Kensaku Mori (Nagoya Univ.) MI2020-17 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
This paper reports a segmentation method of the layered structure of the stomach wall and tumor from μCT volumes using features extracted by Spherical K-means (SpK) and Neural Network (NN). In the proposed method, filters of multi-scale are learned by SpK, and feature extraction is performed from patches. Classification was performed by the NN based on the obtained multi-scale features. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Micro CT / Segmentation / Stomach wall / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 120, no. 156, MI2020-17, pp. 1-6, Sept. 2020. |
Paper # |
MI2020-17 |
Date of Issue |
2020-08-27 (MI) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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MI2020-17 |
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