Appendix

(12240897), Shouhei Hanaoka; (1436338), Yukihiro Nomura; (321592), Naoto Hayashi; (20422110), Issei Sato; (14178017), Soichiro Miki; (321596), Takeharu Yoshikawa; (6387635), Hisaichi Shibata; (20422113), Takahiro Nakao; (20422116), Tomomi Takenaga; (10993207), Hiroaki Koyama; (20422119), Shinichi Cho; (20422122), Noriko Kanemaru; (5075246), Kotaro Fujimoto; (205073), Naoya Sakamoto; (20422125), Tomoya Nishiyama; (673194), Hirotaka Matsuzaki; (381131), Nobutake Yamamichi; (156336), Osamu Abe

doi:10.1371/journal.pone.0315646.s001

Public

Appendix.

Published in Figshare • Dec 12, 2024

Authors:

Shouhei Hanaoka (12240897)

,

Yukihiro Nomura (1436338)

,

Naoto Hayashi (321592)

Abstract

<div><p>A general-purpose method of emphasizing abnormal lesions in chest radiographs, named EGGPALE (Extrapolative, Generative and General-Purpose Abnormal Lesion Emphasizer), is presented. The proposed EGGPALE method is composed of a flow-based generative model and L-infinity-distance-based extrap...

Subject

Artificial intelligence

Image (mathematics)

Generative model

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