Conference item
Weakly-supervised evidence pinpointing and description
- Abstract:
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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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- Publisher copy:
- 10.1007/978-3-319-59050-9_17
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Authors
Bibliographic Details
- 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
Item Description
- Pubs id:
-
pubs:810739
- UUID:
-
uuid:14ae814d-6adb-4367-89c8-424744342c91
- Local pid:
- pubs:810739
- Deposit date:
- 2017-12-14
Terms of use
- Copyright date:
- 2017
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