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Discovering salient anatomical landmarks by predicting human gaze

Abstract:

Anatomical landmarks are a crucial prerequisite for many medical imaging tasks. Usually, the set of landmarks for a given task is predefined by experts. The landmark locations for a given image are then annotated manually or via machine learning methods trained on manual annotations. In this paper, in contrast, we present a method to automatically discover and localize anatomical landmarks in medical images. Specifically, we consider landmarks that attract the visual attention of humans, whic...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/ISBI45749.2020.9098505

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Balliol College
Role:
Author
ORCID:
0000-0002-8030-3321
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Institution:
University of Oxford
Division:
MSD
Department:
Women's & Reproductive Health
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Publisher:
IEEE Publisher's website
Publication date:
2020-05-22
Acceptance date:
2020-01-06
Event title:
IEEE International Symposium on Biomedical Imaging 2020 (ISBI 2020)
Event location:
Iowa City, Iowa, United States
Event start date:
2020-04-03T00:00:00Z
Event end date:
2020-04-07T00:00:00Z
DOI:
EISBN:
9781538693308
EISSN:
1945-8452
ISSN:
1945-7928
ISBN:
9781538693315
Language:
English
Keywords:
Pubs id:
1083710
Local pid:
pubs:1083710
Deposit date:
2020-01-29

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