Segmentation Of Regions In The Medial Temporal Lobe |
| | Abstract | This thesis describes a method used to construct a segmentation algorithm for the Medial Temporal Lobe (MTL) in the human brain. The regions of interest in the MTL consists of four closely connected cortical areas, hippocampus and amygdala. A set consisting of 13 MRI scans of different individuals with matching manual expert annotations of the MTL were delivered, and the intensity images was standardized across all 13 images to get corresponding intensity values for corresponding tissue types.
The regions of the MTL are located fairly deep in the brain where the contrast is quite low, and region-boundaries can be diffecult to find. Many classical segmentation approaches will fail to segment these regions of interest, and the key to a more successful segmentation is incorporation of prior knowledge. The manual annotations are represented as Level Set Functions, and a coupled statistical shape model is trained to capture the spatial variation across the dataset. This model is employed in a region-based energy formulation which maximizes the mutual information between the region labels and the image voxel intensity values of the image. A rather signi cant improvement is seen when the coupled model is compared to individual segmentations of each region. | | Type | Master's thesis [Academic thesis] | | Year | 2007 | | Publisher | Informatics and Mathematical Modelling, Technical University of Denmark, DTU | | Address | Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby | | Series | IMM-Thesis-2007-48 | | Note | Supervised by Assoc. Prof. Rasmus Larsen, IMM, DTU. | | Electronic version(s) | [pdf] | | BibTeX data | [bibtex] | | IMM Group(s) | Image Analysis & Computer Graphics |
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