An interactive tool for segmentation, visualization, and navigation of magnetic resonance images

Authors:
Alan Faulkner;Suchendra Bhandarkar
Affiliations:
Department of Computer Science, University of Georgia, Athens, GA;Department of Computer Science, University of Georgia, Athens, GA
Venue:
CBMS'03 Proceedings of the 16th IEEE conference on Computer-based medical systems
Year:
2003

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Self-Organizing Maps

Self-Organizing Maps
Segmentation of Multispectral MR Images Using a Hierarchical Self-Organizing Map

CBMS '01 Proceedings of the Fourteenth IEEE Symposium on Computer-Based Medical Systems

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Abstract

An interactive tool for the segmentation, visualization and navigation of magnetic resonance (MR) images is presented. Previous work has shown the hierarchical self-organizing map (HSOM) to be highly effective in segmenting MR images at multiple scales or levels of abstraction. The resulting abstraction tree represents the multiscale segmentation of the MR image. A segmented MR image at any desired scale or level of detail can be obtained by appropriate traversal of the abstraction tree. The interactive tool permits traversal of the abstraction tree using a user-friendly graphical user interface (GUI) allowing the user to view the segmented MR image or any portion thereof at the desired level of detail. The tool could be used by radiologists to effectively sift through large amounts of MR image data to arrive at accurate diagnoses in an expeditious manner.