Journal article
A deep learning solution for automatic fetal neurosonographic diagnostic plane verification using clinical standard constraints
- Abstract:
-
During routine ultrasound assessment of the fetal brain for biometry estimation and detection of fetal abnormalities, accurate imaging planes must be found by sonologists following a well-defined imaging protocol or clinical standard, which can be difficult for non-experts to do well. This assessment helps provide accurate biometry estimation and the detection of possible brain abnormalities. We describe a machine-learning method to assess automatically that transventricular ultrasound images...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Publisher copy:
- 10.1016/j.ultrasmedbio.2017.07.013
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Authors
Funding
Bibliographic Details
- Publisher:
- Elsevier Publisher's website
- Journal:
- Ultrasound in Medicine and Biology Journal website
- Volume:
- 43
- Issue:
- 12
- Pages:
- 2925-2933
- Publication date:
- 2017-09-28
- Acceptance date:
- 2017-07-17
- DOI:
- EISSN:
-
1879-291X
- ISSN:
-
0301-5629
- Pmid:
-
28958729
- Source identifiers:
-
732807
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
pubs:732807
- UUID:
-
uuid:042475c3-ebff-43ce-aad0-58cd8c3df007
- Local pid:
- pubs:732807
- Deposit date:
- 2017-12-16
Terms of use
- Copyright holder:
- World Federation for Ultrasound in Medicine and Biology
- Copyright date:
- 2017
- Notes:
- © 2017 World Federation for Ultrasound in Medicine and Biology.
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