Segmentation of Brain Tissue from Magnetic Resonance Images

Item

Title: en_US Segmentation of Brain Tissue from Magnetic Resonance Images
Creator: en_US Kapur, Tina
Date: 2004-10-20T20:28:01Z
Date Available: 2004-10-20T20:28:01Z
Date Issued: en_US 1995-01-01
Identifier: en_US AITR-1566
uri: http://hdl.handle.net/1721.1/7067
Abstract: en_US Segmentation of medical imagery is a challenging problem due to the complexity of the images, as well as to the absence of models of the anatomy that fully capture the possible deformations in each structure. Brain tissue is a particularly complex structure, and its segmentation is an important step for studies in temporal change detection of morphology, as well as for 3D visualization in surgical planning. In this paper, we present a method for segmentation of brain tissue from magnetic resonance images that is a combination of three existing techniques from the Computer Vision literature: EM segmentation, binary morphology, and active contour models. Each of these techniques has been customized for the problem of brain tissue segmentation in a way that the resultant method is more robust than its components. Finally, we present the results of a parallel implementation of this method on IBM's supercomputer Power Visualization System for a database of 20 brain scans each with 256x256x124 voxels and validate those against segmentations generated by neuroanatomy experts.
Extent: 19515578 bytes; 2819915 bytes
Format: application/postscript; application/pdf
Language: en_US
Relation: en_US AITR-1566

Item sets: AI Technical Reports (1964 - 2004)