Original title: Detection Of Anatomical Structures In Ct Data Using Convolutional Neural Networks
Authors: Kozlová, Dominika
Document type: Papers
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: This paper deals with a detection of anatomical structures in medical images using convolutional neural networks (CNN). The designed algorithm contains 2 methods for region proposals and CNN for their classification into categories. Output of the CNN is then postprocessed to obtain the detection result. Categories for detection are head, spine, heart, left and right lung, aorta, liver, left and right kidney, spleen and background. For training and validation of the network were created 2 sets of CT data with annotated areas of selected structures.
Keywords: convolutional neural network; detection; region proposal; selective search
Host item entry: Proceedings of the 24th Conference STUDENT EEICT 2018, ISBN 978-80-214-5614-3

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/11012/138211

Permalink: http://www.nusl.cz/ntk/nusl-393397


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Conference materials > Papers