Deep Learning-based Multiclass Segmentation in Aneurysmal Subarachnoid Hemorrhage
Julia Kiewitz,
Orhun Utku Aydin,
Adam Hilbert
et al.
Abstract:IntroductionAneurysmal subarachnoid hemorrhage (aSAH) is a life-threatening condition with a significant variability in patients’ outcomes. Radiographic scores used to assess the extent of SAH or other potentially outcome-relevant pathologies are limited by interrater variability and do not utilize all available information from the imaging. Image segmentation plays an important role in extracting relevant information from images by enabling precise identification and delineation of objects or regions of inter… Show more
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