Conference item
Robust regression of brain maturation from 3D fetal neurosonography using CRNs
- Abstract:
-
We propose a fully three-dimensional Convolutional Regression Network (CRN) for the task of predicting fetal brain maturation from 3D ultrasound (US) data. Anatomical development is modelled as the sonographic patterns visible in the brain at a given gestational age, which are aggregated by the model into a single value: the brain maturation (BM) score. These patterns are learned from 589 3D fetal volumes, and the model is applied to 3D US images of 146 fetal subjects acquired at multiple, et...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Authors
Bibliographic Details
- Publisher:
- Springer, Cham Publisher's website
- Host title:
- OMIA 2017, FIFI 2017: Fetal, Infant and Ophthalmic Medical Image Analysis
- Series:
- Lecture Notes in Computer Science
- Journal:
- OMIA 2017, FIFI 2017: Fetal, Infant and Ophthalmic Medical Image Analysis Journal website
- Volume:
- 10554
- Pages:
- 73-80
- Publication date:
- 2017-09-09
- Acceptance date:
- 2017-07-08
- DOI:
- ISSN:
-
0302-9743
- ISBN:
- 9783319675602
Item Description
- Pubs id:
-
pubs:735123
- UUID:
-
uuid:45acfec8-2eaa-4ebc-8ce3-f19cc7f95cb9
- Local pid:
- pubs:735123
- Source identifiers:
-
735123
- Deposit date:
- 2018-11-08
Terms of use
- Copyright holder:
- Springer International Publishing AG
- Copyright date:
- 2017
- Notes:
- Copyright © 2017 Springer International Publishing AG.
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