Detection Of Anatomical Structures In Ct Data
Using Convolutional Neural Networks

Kozlová, Dominika

Detection Of Anatomical Structures In Ct Data Using Convolutional Neural Networks

Files

eeict2018-194.pdf(765.31 KB)

Date

2018

Authors

Kozlová, Dominika

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

detection, convolutional neural network, region proposal, selective search

Citation

Proceedings of the 24th Conference STUDENT EEICT 2018. s. 194-196. ISBN 978-80-214-5614-3
http://www.feec.vutbr.cz/EEICT/

Document type

Peer-reviewed

Document version

Published version

Language of document

cz

Document licence