Resolution mosaic EM algorithm for medical image segmentation

• Published in: 2009 International Conference on High Performance Computing and Simulation pp. 208 - 215
• Main Authors: Salem, M.A.-M., Meffert, B.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2009
• Subjects: Biomedical imaging; Computer vision; Expectation Maximization; Humans; Image resolution; Image segmentation; Information Relevance; Layout; Magnetic Resonance Images; Multiresolution; Multiresolution analysis; Signal resolution; Spatial resolution; Wavelet; Wavelet transforms
• ISBN: 1424449065; 9781424449064
• DOI: 10.1109/HPCSIM.2009.5192800

Multiresolution analysis is an established part of the human vision system. It builds different representations of an image with a spatial resolution adapted to the size of objects of interest and to its level of relevance. Multiresolution analysis is an efficient tool for image segmentation. It allows the processing of global features as well as local features in a corresponding proper scale. Furthermore, it simplifies the segmentation process, accelerates the computation, and improves the results. In this work we propose a segmentation algorithm that is based on the multiresolution analysis for the magnetic resonance images of the human brain. It has been evaluated against known algorithm from the literature. The image subject to segmentation is preprocessed to be represented in a mosaic of different resolutions, based on the distribution of the information contained in the image. Then the conventional EM algorithm is applied for the segmentation.