Automatic whole brain MRI segmentation of the developing neonatal brain
- Submitting institution
-
Imperial College of Science, Technology and Medicine
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2121
- Type
- D - Journal article
- DOI
-
10.1109/TMI.2014.2322280
- Title of journal
- IEEE Transactions on Medical Imaging
- Article number
- 9
- First page
- 1818
- Volume
- 33
- Issue
- 9
- ISSN
- 0278-0062
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
10.1109/TMI.2014.2322280
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
8
- Research group(s)
-
-
- Citation count
- 140
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper proposes one of the first ever comprehensive brain segmentation algorithms for neonatal brain MR images. We demonstrate that the proposed technique achieves highly accurate results and is very robust across a wide range of neonatal ages, from 24 weeks gestational age to term-equivalent age. The work forms the basis for the structural image analysis pipeline that is used for processing 1500 brain images, publicly released as part of ERC Synergy Developing Human Connectome Project (http://www.developingconnectome.org).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
