Numerical experiments for segmenting medical images using level sets

Abstract

Image segmentation is the process by which objects are separated from background information. Structural segmentation from 2D and 3D images is an important step in the analysis of medical image data. In this technical report, we utilize level set algorithms and active contours without edges to segment two and three-dimensional image data. Besides synthetical data, we also use magnetic resonance images of the human brain provided by the Institute of Biomedical Research in Light and Images of the University of Coimbra (IBILI)