Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection
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
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| Format: | Article |
| Language: | English |
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International Society for Computer Aided Surgery (ISCAS)
2015
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| Online Access: | http://ir.unimas.my/11960/ http://ir.unimas.my/11960/ http://ir.unimas.my/11960/ http://ir.unimas.my/11960/1/No%208%20%28abstrak%29.pdf |
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unimas-11960 |
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eprints |
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unimas-119602017-02-21T01:05:41Z http://ir.unimas.my/11960/ Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection Kuryati, Kipli Abbas, Z. Kouzani T Technology (General) 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 International Society for Computer Aided Surgery (ISCAS) 2015-11-25 Article PeerReviewed text en http://ir.unimas.my/11960/1/No%208%20%28abstrak%29.pdf Kuryati, Kipli and Abbas, Z. Kouzani (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, 10 (7). pp. 1003-1016. ISSN 1861-6410 http://www.cars-int.org/cars_journal/journal_of_cars.html 10.1007/s11548-014-1130-9 |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
Universiti Malaysia Sarawak |
| building |
UNIMAS Institutional Repository |
| collection |
Online Access |
| language |
English |
| topic |
T Technology (General) |
| spellingShingle |
T Technology (General) Kuryati, Kipli Abbas, Z. Kouzani Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection |
| description |
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 |
| format |
Article |
| author |
Kuryati, Kipli Abbas, Z. Kouzani |
| author_facet |
Kuryati, Kipli Abbas, Z. Kouzani |
| author_sort |
Kuryati, Kipli |
| title |
Degree of contribution (DoC) feature selection algorithm
for structural brain MRI volumetric features in depression
detection |
| title_short |
Degree of contribution (DoC) feature selection algorithm
for structural brain MRI volumetric features in depression
detection |
| title_full |
Degree of contribution (DoC) feature selection algorithm
for structural brain MRI volumetric features in depression
detection |
| title_fullStr |
Degree of contribution (DoC) feature selection algorithm
for structural brain MRI volumetric features in depression
detection |
| title_full_unstemmed |
Degree of contribution (DoC) feature selection algorithm
for structural brain MRI volumetric features in depression
detection |
| title_sort |
degree of contribution (doc) feature selection algorithm
for structural brain mri volumetric features in depression
detection |
| publisher |
International Society for Computer Aided Surgery (ISCAS) |
| publishDate |
2015 |
| url |
http://ir.unimas.my/11960/ http://ir.unimas.my/11960/ http://ir.unimas.my/11960/ http://ir.unimas.my/11960/1/No%208%20%28abstrak%29.pdf |
| first_indexed |
2018-09-06T15:57:00Z |
| last_indexed |
2018-09-06T15:57:00Z |
| _version_ |
1610874272351256576 |