Original title: Detection Of Intracranial Haemorrhages In Head Ct Data Based On Deep Learning
Authors: Nemček, Jakub
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: In this paper, we present a method for detection of intracranial haemorrhages in the head CT data using convolutional neural networks. We introduce three 2D image classifiers that perform in three perpendicular anatomical planes and classify the CT slices into healthy or pathological, whereby they provide the information about the position of the haemorrhage in the 3D CT image. The accuracies of the three models are 90.19%, 88.15%, and 80.90% for the axial, sagittal and coronal plane.
Keywords: classification; convolutional neural network; CT; detection; Intracranial haemorrhage
Host item entry: Proceedings II of the 26st Conference STUDENT EEICT 2020: Selected papers, ISBN 978-80-214-5868-0

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/11012/200623

Permalink: http://www.nusl.cz/ntk/nusl-447675


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