Title :
Computer-aided detection of depression from magnetic resonance images
Author :
Kipli, Kuryati ; Kouzani, Abbas Z. ; Joordens, Matthew
Author_Institution :
Sch. of Eng., Deakin Univ., Waurn Ponds, VIC, Australia
Abstract :
Magnetic resonance imaging (MRI) of the brain is used to detect depression disorder. However, a large number of MRI scans needs to be analyzed for such detection. Manual segmentation of the biomarkers in MRI scans by clinical experts can become time consuming and sometimes erroneous. This paper presents a study on computer-aided detection of depression from MRI scans. These systems have not yet been identified, categorized and compared in the literature. The paper covers fully automated to semi-automated detection systems. It also presents performance comparison for the considered systems.
Keywords :
biomedical MRI; brain; computer aided analysis; image segmentation; medical disorders; medical image processing; neurophysiology; psychology; MRI; biomarker segmentation; brain; computer aided detection; depression disorder; fully automated detection systems; magnetic resonance images; semi-automated detection systems; Biomedical imaging; Brain modeling; Computational modeling; Image segmentation; Magnetic resonance imaging; Manuals; Sensitivity; Depression; computer aided detection; magnetic resonance images;
Conference_Titel :
Complex Medical Engineering (CME), 2012 ICME International Conference on
Conference_Location :
Kobe
Print_ISBN :
978-1-4673-1617-0
DOI :
10.1109/ICCME.2012.6275745
