Automated, anatomy-based, heuristic post-processing reduces false positives and improves interpretability of deep learning intracranial aneurysm detection models

Jisoo Kim; Alberto Ceballos-Arroyo; Chu-Hsuan Lin; Ping Liu; Huaizu Jiang; Shrikanth Yadav; Qi Wan; Lei Qin; Geoffrey S. Young

doi:10.1038/s41598-025-33083-7

Automated, anatomy-based, heuristic post-processing reduces false positives and improves interpretability of deep learning intracranial aneurysm detection models

J Jisoo Kim A Alberto Ceballos-Arroyo C Chu-Hsuan Lin P Ping Liu (Chemistry Department) H Huaizu Jiang S Shrikanth Yadav Q Qi Wan L Lei Qin (Department of Chemistry) G Geoffrey S. Young

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Article Details

Journal Scientific Reports

Volume / Issue Vol. 16, Issue 1

Published December 22, 2025

DOI 10.1038/s41598-025-33083-7

ISSN 2045-2322

Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (9)

J

Jisoo Kim

A

Alberto Ceballos-Arroyo

C

Chu-Hsuan Lin

P

Ping Liu

Chemistry Department

H

Huaizu Jiang

S

Shrikanth Yadav

Q

Qi Wan

L

Lei Qin

Department of Chemistry

G

Geoffrey S. Young

Automated, anatomy-based, heuristic post-processing reduces false positives and improves interpretability of deep learning intracranial aneurysm detection models

Article Details

Journal Info

Authors (9)

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