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Conference item

Weakly-supervised evidence pinpointing and description

Abstract:

We propose a learning method to identify which specific regions and features of images contribute to a certain classification. In the medical imaging context, they can be the evidence regions where the abnormalities are most likely to appear, and the discriminative features of these regions supporting the pathology classification. The learning is weakly-supervised requiring only the pathological labels and no other prior knowledge. The method can also be applied to learn the salient descripti...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MSD
Department:
RDM
Sub department:
RDM Cardiovascular Medicine
Role:
Author
Publisher:
Springer Publisher's website
Journal:
25th International Conference on Information Processing in Medical Imaging (IPMI 2017) Journal website
Host title:
25th International Conference on Information Processing in Medical Imaging (IPMI 2017)
Publication date:
2017-05-01
Acceptance date:
2017-02-10
DOI:
Source identifiers:
810739
Pubs id:
pubs:810739
UUID:
uuid:14ae814d-6adb-4367-89c8-424744342c91
Local pid:
pubs:810739
Deposit date:
2017-12-14

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