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Titel:

Physiology-Based Simulation of the Retinal Vasculature Enables Annotation-Free Segmentation of OCT Angiographs

Dokumenttyp:
Proceedings Paper
Autor(en):
Menten, Martin J.; Paetzold, Johannes C.; Dima, Alina; Menze, Bjoern H.; Knier, Benjamin; Rueckert, Daniel
Abstract:
Optical coherence tomography angiography (OCTA) can non-invasively image the eye's circulatory system. In order to reliably characterize the retinal vasculature, there is a need to automatically extract quantitative metrics from these images. The calculation of such biomarkers requires a precise semantic segmentation of the blood vessels. However, deep-learning-based methods for segmentation mostly rely on supervised training with voxel-level annotations, which are costly to obtain. In this w...     »
Zeitschriftentitel:
Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv
Jahr:
2022
Band / Volume:
13438
Seitenangaben Beitrag:
330-340
Volltext / DOI:
doi:10.1007/978-3-031-16452-1_32
Print-ISSN:
0302-9743
TUM Einrichtung:
Institut für KI und Informatik in der Medizin (Prof. Rückert)
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