Towards automated detection of depression from brain structural magnetic resonance images

Neuroradiology

Volumn 55, Issue 5, 2013, Pages 567-584

  Kipli, Kuryati ^a,b   Kouzani, Abbas Z ^a   Williams, Lana J ^a  

^a DEAKIN UNIVERSITY   (Australia)

^b UNIVERSITI MALAYSIA SARAWAK   (Malaysia)

Author keywords

Classification; Depression; Image processing; Magnetic resonance imaging; Pattern recognition

Indexed keywords

BIOLOGICAL MARKER;

ALGORITHM; AREA UNDER THE CURVE; ARTICLE; AUTOANALYSIS; BIPOLAR DISORDER; BLOOD EXAMINATION; CLINICAL FEATURE; COMPUTER ASSISTED DIAGNOSIS; DEPRESSION; DIAGNOSTIC ACCURACY; DISEASE CLASSIFICATION; DYSTHYMIA; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; INTERMETHOD COMPARISON; MAJOR DEPRESSION; MEDICAL HISTORY; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSICAL EXAMINATION; PRIORITY JOURNAL; PROGNOSIS; PSYCHIATRIC TREATMENT; RECEIVER OPERATING CHARACTERISTIC; SEASONAL AFFECTIVE DISORDER; SENSITIVITY AND SPECIFICITY; STRUCTURAL MAGNETIC RESONANCE IMAGING; STRUCTURE ANALYSIS; VOLUMETRY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; DEPRESSION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84878729599     PISSN: 00283940     EISSN: 14321920     Source Type: Journal    
DOI: 10.1007/s00234-013-1139-8     Document Type: Article

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