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, ...
Searching digital biomedical images is a challenging problem. Prevalent retrieval techniques involve human-supplied text annotations to describe image contents. Biomedical images,...
—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....
Three different systematic approaches to generate multiple classifiers in atlas-based biomedical image segmentation are compared. Different atlases, as well as different parametri...
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...