Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection
Version 2 2024-06-03, 12:40
Version 1 2015-02-23, 15:45
journal contribution
posted on 2024-06-03, 12:40 authored by K Kipli, Abbas KouzaniAbbas KouzaniAccurate 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.
History
Journal
International Journal of Computer Assisted Radiology and SurgeryVolume
10Pagination
1003-1016Location
GermanyPublisher DOI
ISSN
1861-6410eISSN
1861-6429Language
engPublication classification
C Journal article, C1 Refereed article in a scholarly journalCopyright notice
2014, SpringerIssue
7Publisher
SPRINGER HEIDELBERGUsage metrics
Keywords
Science & TechnologyTechnologyLife Sciences & BiomedicineEngineering, BiomedicalRadiology, Nuclear Medicine & Medical ImagingSurgeryEngineeringFeature selectionEnsembleDepression detectionBrain sMRI dataVolumetric featuresDegree of contributionWHITE-MATTER LESIONSORBITOFRONTAL CORTEX VOLUMELATE-LIFE DEPRESSIONHIPPOCAMPAL VOLUMESCLASSIFICATIONPREDICTIONDISEASEHYPERINTENSITIESPOLYMORPHISMSOPTIMIZATION970109 Expanding Knowledge in EngineeringSchool of Engineering090609 Signal Processing
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