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Shit, S.* ; Ezhov, I.* ; Paetzold, J.C. ; Menze, B.*

A ν -Net: Automatic detection and segmentation of aneurysm.

In: International workshop on Cerebral Aneurysm Detection. Berlin [u.a.]: Springer, 2021. 51-57 (Lect. Notes Comput. Sc. ; 12643 LNCS)
DOI Verlagsversion bestellen
We propose an automatic solution for the CADA 2020 challenge to detect aneurysm from Digital Subtraction Angiography (DSA) images. Our method relies on 3D U-net as the backbone and heavy data augmentation with a carefully chosen loss function. We were able to generalize well using our solution (despite training on a small dataset) that is demonstrated through accurate detection and segmentation on the test data.
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Publikationstyp Artikel: Sammelbandbeitrag/Buchkapitel
Schlagwörter Aneurysm ; Detection ; Segmentation
ISSN (print) / ISBN 0302-9743
e-ISSN 1611-3349
Bandtitel International workshop on Cerebral Aneurysm Detection
Quellenangaben Band: 12643 LNCS, Heft: , Seiten: 51-57 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort Berlin [u.a.]
Institut(e) Institute for Tissue Engineering and Regenerative Medicine (ITERM)