A Robust and Accurate Deep-learning-based Method for the Segmentation of Subcortical Brain: Cross-dataset Evaluation of Generalization Performance
Author:
Affiliation:
1. Graduate School of Engineering, Kyoto University
Publisher
Japanese Society for Magnetic Resonance in Medicine
Subject
Radiology Nuclear Medicine and imaging
Link
https://www.jstage.jst.go.jp/article/mrms/20/2/20_mp.2019-0199/_pdf
Reference27 articles.
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2. 2. Okada N, Fukunaga M, Yamashita F, et al. Abnormal asymmetries in subcortical brain volume in schizophrenia. Mol Psychiatry 2016; 21:1460–1466.
3. 3. Goldman S, O’Brien LM, Filipek PA, Rapin I, Herbert MR. Motor stereotypies and volumetric brain alterations in children with autistic disorder. Res Autism Spectr Disord 2013; 7:82–92.
4. 4. Geevarghese R, Lumsden DE, Hulse N, Samuel M, Ashkan K. Subcortical structure volumes and correlation to clinical variables in Parkinson’s disease. J Neuroimaging 2015; 25:275–280.
5. 5. Morey RA, Selgrade ES, Wagner HR, Huettel SA, Wang L, McCarthy G. Scan-rescan reliability of subcortical brain volumes derived from automated segmentation. Hum Brain Mapp 2010; 31:1751–1762.
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