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Gerl, S.* ; Paetzold, J.C.* ; He, H. ; Ezhov, I.* ; Shit, S.* ; Kofler, F.* ; Bayat, A.A.* ; Tetteh, G.* ; Ntziachristos, V. ; Menze, B.*

A distance-based loss for smooth and continuous skin layer segmentation in optoacoustic images.

Lect. Notes Comput. Sc. 12266 LNCS, 309-319 (2020)
DOI
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Raster-scan optoacoustic mesoscopy (RSOM) is a powerful, non-invasive optical imaging technique for functional, anatomical, and molecular skin and tissue analysis. However, both the manual and the automated analysis of such images are challenging, because the RSOM images have very low contrast, poor signal to noise ratio, and systematic overlaps between the absorption spectra of melanin and hemoglobin. Nonetheless, the segmentation of the epidermis layer is a crucial step for many downstream medical and diagnostic tasks, such as vessel segmentation or monitoring of cancer progression. We propose a novel, shape-specific loss function that overcomes discontinuous segmentations and achieves smooth segmentation surfaces while preserving the same volumetric Dice and IoU. Further, we validate our epidermis segmentation through the sensitivity of vessel segmentation. We found a 20% improvement in Dice for vessel segmentation tasks when the epidermis mask is provided as additional information to the vessel segmentation network.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Sprache englisch
Veröffentlichungsjahr 2020
HGF-Berichtsjahr 2020
ISSN (print) / ISBN 0302-9743
e-ISSN 1611-3349
Quellenangaben Band: 12266 LNCS, Heft: , Seiten: 309-319 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort Berlin [u.a.]
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-505500-001
Scopus ID 85092792329
Erfassungsdatum 2020-10-25