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Automated myocardial wall motion classification using handcrafted features vs a deep CNN-based mapping

Abstract:

Compared to other modalities such as computed tomography or magnetic resonance imaging, the appearance of ultrasound images is highly dependent on the expertise of the sonographer or clinician making the image acquisition, as well as the machine used, making it a challenge to analyze due to the frequent presence of artefacts, missing boundaries, attenuation, shadows, and speckle. In addition, manual contouring of the epicardial and endocardial walls exhibits large inconsistencies and variatio...

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Publication status:
Published
Peer review status:
Reviewed (other)

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Publisher copy:
10.1109/embc.2018.8513063

Authors


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Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
RDM
Sub department:
RDM Cardiovascular Medicine
Role:
Author
Publisher:
IEEE Publisher's website
Host title:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Journal:
Annual International Conference of the IEEE Engineering in Medicine and Biology Societymedicin Journal website
Volume:
2018
Pages:
3140-3143
Publication date:
2018-10-29
Acceptance date:
2018-07-17
Event location:
United States
DOI:
ISSN:
1557-170X
Pmid:
30441060
ISBN:
9781538636466
Keywords:
Pubs id:
pubs:952315
UUID:
uuid:66aa8ba4-7a27-421c-9456-621074bd5684
Local pid:
pubs:952315
Source identifiers:
952315
Deposit date:
2019-05-23

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