| Description |
1 CD-ROM (PDF file (xvii, 143 pages, illustrations)) ; 12 cm |
|
4 3/4 in |
| Summary |
Summary: Automated sMRI-based depression detection system is developed whose components include acquisition and preprocessing, feature extraction, feature selection, and classification. The core focus of the research is on the establishment of a new feature selection algorithm that quantifies the most relevant brain volumetric feature for depression detection at an individual level |
| Notes |
Submitted to the School of Engineering in the Faculty of Science, Engineering and Built Environment, Deakin University |
|
Thesis (Ph.D.) -- Deakin University, Victoria, 2014 |
| Bibliography |
Bibliography: 123-143 pages |
| Subject |
Depressions -- Research.
|
|
Mental illness -- Diagnosis.
|
|
Magnetic resonance imaging.
|
| Genre/Form |
Academic theses.
|
| Author |
Deakin University. Faculty of Science, Engineering and Built Environment
|
|
Deakin University. School of Engineering, degree granting institution
|
|
