Presentation 2023-09-08
A Study on Identifying Gender Differences Using Deep Learning from Retinal Fundus Images
Shota Tsutsui, Ichiro Maruko, Moeko Kawai, Yoichi Kato, Jun Ohya,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Previous studies show that a properly designed and trained deep learning algorithm is capable to identify the gender of a person from the person's fundus images although the obvious difference in male and female fundus images is unknown. In this paper, we extend LIME, one of the Explainable AI, to RGB channels, and consider the regions (obtained by segmentation into super-pixels) and colors as a basis for deep learning classification. The results of Mann-Whitney's U test on the color of the classification basis area suggested that there were slight color differences by gender in certain areas of the fundus image (e.g., optic disc), similar to the results shown by LIME extended to RGB.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Explainable AI / Retina fundus images / Deep learning / LIME
Paper # MI2023-17
Date of Issue 2023-09-01 (MI)

Conference Information
Committee MI
Conference Date 2023/9/8(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Ryo Haraguchi(Univ. of Hyogo)
Vice Chair Hideaki Haneishi(Chiba Univ.) / Takayuki Kitasaka(Aichi Inst. of Tech.)
Secretary Hideaki Haneishi(Yamaguchi Univ.) / Takayuki Kitasaka(NAIST)
Assistant Takeshi Hara(Gifu Univ.) / Kenichi Morooka(Okayama Univ.)

Paper Information
Registration To Technical Committee on Medical Imaging
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Study on Identifying Gender Differences Using Deep Learning from Retinal Fundus Images
Sub Title (in English)
Keyword(1) Explainable AI
Keyword(2) Retina fundus images
Keyword(3) Deep learning
Keyword(4) LIME
1st Author's Name Shota Tsutsui
1st Author's Affiliation Waseda University(Waseda Univ.)
2nd Author's Name Ichiro Maruko
2nd Author's Affiliation Tokyo Women's Medical University(TWMU)
3rd Author's Name Moeko Kawai
3rd Author's Affiliation Tokyo Women's Medical University(TWMU)
4th Author's Name Yoichi Kato
4th Author's Affiliation Waseda University(Waseda Univ.)
5th Author's Name Jun Ohya
5th Author's Affiliation Waseda University(Waseda Univ.)
Date 2023-09-08
Paper # MI2023-17
Volume (vol) vol.123
Number (no) MI-185
Page pp.pp.8-11(MI),
#Pages 4
Date of Issue 2023-09-01 (MI)