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MICCAI
2005
Springer

Spectral Clustering Algorithms for Ultrasound Image Segmentation

9 years 3 months ago
Spectral Clustering Algorithms for Ultrasound Image Segmentation
Abstract. Image segmentation algorithms derived from spectral clustering analysis rely on the eigenvectors of the Laplacian of a weighted graph obtained from the image. The NCut criterion was previously used for image segmentation in supervised manner. We derive a new strategy for unsupervised image segmentation. This article describes an initial investigation to determine the suitability of such segmentation techniques for ultrasound images. The extension of the NCut technique to the unsupervised clustering is first described. The novel segmentation algorithm is then performed on simulated ultrasound images. Tests are also performed on abdominal and fetal images with the segmentation results compared to manual segmentation. Comparisons with the classical NCut algorithm are also presented. Finally, segmentation results on other types of medical images are shown.
Neculai Archip, Robert Rohling, Peter Cooperberg,
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where MICCAI
Authors Neculai Archip, Robert Rohling, Peter Cooperberg, Hamid Tahmasebpour, Simon K. Warfield
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