Multiscale Edge Detection and Segmentation Algorithms for Biomedical Image Analysis

Ronen Basri
Weizmann Institute of Science

Algorithms for regions and boundary detection in images are important for biomedical data analysis both for research and diagnosis. In this talk I will present algorithms for edge detection and segmentation that use a multiscale approach to overcome problems of noise and poor contrast, which are common in biomedical images. Our edge detection algorithm is based on a fast method for computing filter responses at different lengths and orientations and on a recursive decision process which selects the desired responses from all scales. Our image segmentation algorithm combines intensity and texture cues and outputs a full hierarchy of segments. These tools were applied to a variety of biomedical images acquired by light and electron microscopes and by Magnetic Resonance Scanners, and tested on a variety of applications including the identification of cell structures, tissues, and abnormal lesions.

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