The parallel watershed transformation used in grayscale image segmentation is here augmented to perform with the aid of a priori supplied image cues, called markers. The reason for introducing markers is to calibrate a resilient algorithm to oversegmenta-tion. In a hybrid fashion, pixels are rst clustered based on spatial proximity and graylevel homogeneity with the watershed transformation. Bo...

Background Computer Aided Diagnosis (CAD) systems have been developing in the last years with aim of helping diagnosis and monitoring several diseases. We present a novel CAD system based on hybrid Watershed-Clustering algorithm for detection lesions Multiple Sclerosis. Methods Magnetic Resonance Imaging scans (FLAIR sequences without gadolinium) 20 patients affected by Sclerosis hyperintense w...

A new method for image segmentation is proposed in this paper, which combines the watershed transform, KFCM and level set method. The watershed transform is first used to presegment the image so as to get the initial partition of it. Some useful information of the primitive regions and boundaries can be obtained. The kernel fuzzy c-means (KFCM) was used to generate an initial contour curve whic...

Protein spot detection is an important step in gel image analysis. The results of spot detection may substantially influence gel image analysis. One of the most challenges of spot detection is separation of spots from complex region, where spots are overlapped and saturated. In this paper, we propose a spot detection algorithm which is capable of detection of spots from complex region. The prop...

This paper deals with mathematical properties of watersheds in weighted graphs linked to region merging methods, as used in image analysis. In a graph, a cleft (or a binary watershed) is a set of vertices that cannot be reduced, by point removal, without changing the number of regions (connected components) of its complement. To obtain a watershed adapted to morphological region merging, it has...