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Recurrent neural networks for aortic image sequence segmentation with sparse annotations
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![]() | Accepted version | 828.45 kB | Adobe PDF | View/Open |
Title: | Recurrent neural networks for aortic image sequence segmentation with sparse annotations |
Authors: | Bai, W Suzuki, H Qin, C Tarroni, G Oktay, O Matthews, PM Rueckert, D |
Item Type: | Conference Paper |
Abstract: | Segmentation of image sequences is an important task in medical image analysis, which enables clinicians to assess the anatomy and function of moving organs. However, direct application of a segmentation algorithm to each time frame of a sequence may ignore the temporal continuity inherent in the sequence. In this work, we propose an image sequence segmentation algorithm by combining a fully convolutional network with a recurrent neural network, which incorporates both spatial and temporal information into the segmentation task. A key challenge in training this network is that the available manual annotations are temporally sparse, which forbids end-to-end training. We address this challenge by performing non-rigid label propagation on the annotations and introducing an exponentially weighted loss function for training. Experiments on aortic MR image sequences demonstrate that the proposed method significantly improves both accuracy and temporal smoothness of segmentation, compared to a baseline method that utilises spatial information only. It achieves an average Dice metric of 0.960 for the ascending aorta and 0.953 for the descending aorta. |
Issue Date: | 16-Sep-2018 |
Date of Acceptance: | 25-May-2018 |
URI: | http://hdl.handle.net/10044/1/64136 |
DOI: | https://dx.doi.org/10.1007/978-3-030-00937-3_67 |
ISBN: | 9783030009366 |
ISSN: | 0302-9743 |
Publisher: | Springer Nature Switzerland AG |
Start Page: | 586 |
End Page: | 594 |
Journal / Book Title: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Volume: | 11073 LNCS |
Copyright Statement: | © 2018 Springer-Verlag. The final publication is available at Springer via https://dx.doi.org/10.1007/978-3-030-00937-3_67 |
Sponsor/Funder: | Imperial College Healthcare NHS Trust- BRC Funding Engineering & Physical Science Research Council (EPSRC) UK DRI Ltd |
Funder's Grant Number: | RD410 EP/N014529/1 N/A |
Conference Name: | International Conference On Medical Image Computing & Computer Assisted Intervention |
Keywords: | cs.CV 08 Information And Computing Sciences Artificial Intelligence & Image Processing |
Publication Status: | Published |
Start Date: | 2018-09-16 |
Finish Date: | 2018-09-20 |
Conference Place: | Granada, Spain |
Online Publication Date: | 2018-09-13 |
Appears in Collections: | Computing Department of Medicine (up to 2019) |