Original title: Object Detection Networks For Localization And Classification Of Intracranial Hemorrhages
Authors: Nemcek, Jakub
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: Intracranial hemorrhages represent life-threatening brain injuries. This paper presents twostate-of-the-art object detection systems (Faster R-CNN and YOLO v2) which are trained to localizeand classify hemorrhages in axial head CT slices by providing labelled rectangular bounding boxes.Publicly available datasets of head CT data and ground truth bounding boxes are used to evaluate andcompare the performance of both detectors. The Faster R-CNN shows better results by achieving anaverage Jaccard coefficient of 58.7 %.
Keywords: classification; computedtomography; convolutional neural network; Faster R-CNN; intracranial hemorrhage; localization; YOLO v2
Host item entry: Proceedings II of the 27st Conference STUDENT EEICT 2021: Selected papers, ISBN 978-80-214-5943-4

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/200824

Permalink: http://www.nusl.cz/ntk/nusl-447868


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