Paper Abstract and Keywords |
Presentation |
2021-03-15 11:00
Improvement of a skeletal recognition algorithm of bone scintigrams Yuri Hoshino, Atsushi Saito (TUAT), Atsushi Yoshida, Shigeaki Higashiyama, Joji Kwabe (Osaka City Univ), Hiromitsu Daisaki (GCHS), Kazuhiro Nishikawa (NMP), Akinobu Shimizu (TUAT) MI2020-47 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In this paper, we report the results of our work on skeletal recognition processing on bone scintigram. Specifically, we report the results of a study of loss design that takes into account the topological features of bone regions in order to improve anatomically unnatural recognition results. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
bone scintigram / segmentation / diagnostic support / deep learning / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 120, no. 431, MI2020-47, pp. 1-2, March 2021. |
Paper # |
MI2020-47 |
Date of Issue |
2021-03-08 (MI) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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MI2020-47 |
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