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Deep learning for biomedical texture image analysis

Andrearczyk, Vincent and Whelan, Paul F. orcid logoORCID: 0000-0001-9230-7656 (2017) Deep learning for biomedical texture image analysis. In: Irish Machine Vision and Image Processing Conference 2017, 30 Aug - 1 Sept 2017, Maynooth, Ireland. ISBN 978-0-9934207-2-6

Abstract
This paper shows promising results in the application of Convolutional Neural Networks (CNN) to biomedical imaging. Texture is often dominant in biomedical imaging and its analysis is essential to automatically obtain meaningful information. Therefore, we introduce a method using a Texture CNN for the classification of biomedical images. We test our approach on three datasets of liver tissues images and significantly improve the state of the art.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:computer vision; Deep Learning; Image Analysis; Texture Analysis; Biomedical Image Analysis
Subjects:Computer Science > Machine learning
Engineering > Signal processing
Computer Science > Image processing
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Published in: McDonald, John, Markham, Charles and Winstanley, Adam C., (eds.) Irish Machine Vision and Image Processing Conference Proceedings 2017. . Irish Pattern Recognition & Classification Society (IPRCS). ISBN 978-0-9934207-2-6
Publisher:Irish Pattern Recognition & Classification Society (IPRCS)
Official URL:http://eprints.maynoothuniversity.ie/8841/1/IMVIP2...
Copyright Information:© 2017 IPRCS
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:22090
Deposited On:27 Oct 2017 11:15 by Paul Whelan . Last Modified 11 Jan 2019 10:31
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