Focusnet: an attention-based fully convolutional network for medical image segmentation

Kaul, C., Manandhar, S. and Pears, N. (2019) Focusnet: an attention-based fully convolutional network for medical image segmentation. In: IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), Venice, Italy, 8-11 April 2019, pp. 455-458. ISBN 9781538636411 (doi: 10.1109/ISBI.2019.8759477)

Abstract

We propose a novel technique to incorporate attention within convolutional neural networks using feature maps generated by a separate convolutional autoencoder. Our attention architecture is well suited for incorporation with deep convolutional networks. We evaluate our model on benchmark segmentation datasets in skin cancer segmentation and lung lesion segmentation. Results show highly competitive performance when compared with U-Net and it's residual variant.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Kaul, Dr Chaitanya
• Authors: Kaul, C., Manandhar, S., and Pears, N.
• College/School: College of Science and Engineering > School of Computing Science
• ISSN: 1945-8452
• ISBN: 9781538636411
• Published Online: 11 July 2019
• Copyright Holders: Copyright © 2019 IEEE
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

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