Journal article
Improving cardiac MRI convolutional neural network segmentation on small training datasets and dataset shift: A continuous kernel cut approach
- Abstract:
-
Cardiac magnetic resonance imaging (MRI) provides a wealth of imaging biomarkers for cardiovascular disease care and segmentation of cardiac structures is required as a first step in enumerating these biomarkers. Deep convolutional neural networks (CNNs) have demonstrated remarkable success in image segmentation but typically require large training datasets and provide suboptimal results that require further improvements. Here, we developed a way to enhance cardiac MRI multi-class segmentatio...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Authors
Funding
Bibliographic Details
- Publisher:
- Elsevier Publisher's website
- Journal:
- Medical Image Analysis Journal website
- Volume:
- 61
- Article number:
- 101636
- Publication date:
- 2020-01-11
- Acceptance date:
- 2020-01-06
- DOI:
- EISSN:
-
1361-8423
- ISSN:
-
1361-8415
- Pmid:
-
31972427
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
1084809
- Local pid:
- pubs:1084809
- Deposit date:
- 2020-03-23
Terms of use
- Copyright holder:
- Elsevier B.V.
- Copyright date:
- 2020
- Rights statement:
- © 2020 Elsevier B.V.
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from Elsevier at https://doi.org/10.1016/j.media.2020.101636
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