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» Segmentation of biomedical images with eigenvectors
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MICCAI
2005
Springer
9 years 4 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 cr...
Neculai Archip, Robert Rohling, Peter Cooperberg, ...
MM
2000
ACM
159views Multimedia» more  MM 2000»
9 years 3 months ago
Region-based retrieval of biomedical images
Searching digital biomedical images is a challenging problem. Prevalent retrieval techniques involve human-supplied text annotations to describe image contents. Biomedical images,...
James Ze Wang
PAMI
2007
202views more  PAMI 2007»
8 years 11 months ago
Weighted Graph Cuts without Eigenvectors A Multilevel Approach
—A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
ISBI
2004
IEEE
10 years 3 days ago
Performance-Based Multi-Classifier Decision Fusion for Atlas-Based Segmentation of Biomedical Images
Combinations of multiple classifiers have been found to be consistently more accurate than a single classifier. The construction of multiple independent classifiers, however, is t...
Torsten Rohlfing, Daniel B. Russakoff, Calvin R. M...
CVPR
2004
IEEE
10 years 1 months ago
Multi-Classifier Framework for Atlas-Based Image Segmentation
Three different systematic approaches to generate multiple classifiers in atlas-based biomedical image segmentation are compared. Different atlases, as well as different parametri...
Torsten Rohlfing, Calvin R. Maurer Jr.
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