An application of geometric active contour in bio-medical engineering

Segmentation and boundary detection is one of the most important task in image processing. In segmentation, an image is partitioned into a set of distinct regions. This is an intermediate step in various image processing applications like content based image and video retrieval, object recognition and tracking, and biomedical engineering etc. In this paper, we implemented an geometric active contour model which uses level set methods and an energy function, by minimizing it we can evolve the boundary of an object. This algorithm does not depend on the gradient of the image, so its performance is good for noisy images also. It can be used to detect lesion or tumor in an MRI image.