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Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection

Kipli, Kuryati and Kouzani, Abbas Z. 2015, Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection, International journal of computer assisted radiology and surgery, vol. 10, no. 7, pp. 1003-1016, doi: 10.1007/s11548-014-1130-9.

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Title Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection
Author(s) Kipli, Kuryati
Kouzani, Abbas Z.
Journal name International journal of computer assisted radiology and surgery
Volume number 10
Issue number 7
Start page 1003
End page 1016
Total pages 14
Publisher Springer
Place of publication Berlin, Germany
Publication date 2015-07
ISSN 1861-6429
Keyword(s) Brain sMRI data
Degree of contribution
Depression detection
Ensemble
Feature selection
Volumetric features
Summary Accurate detection of depression at an individual level using structural magnetic resonance imaging (sMRI) remains a challenge. Brain volumetric changes at a structural level appear to have importance in depression biomarkers studies. An automated algorithm is developed to select brain sMRI volumetric features for the detection of depression.
Language eng
DOI 10.1007/s11548-014-1130-9
Field of Research 090609 Signal Processing
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, Springer
Persistent URL http://hdl.handle.net/10536/DRO/DU:30069943

Document type: Journal Article
Collection: School of Engineering
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