DocumentCode :
2799249
Title :
Resolution mosaic EM algorithm for medical image segmentation
Author :
Salem, Mohammed A-Megeed ; Meffert, Beate
Author_Institution :
Fac. of Comput. & Inf. Sci., Ain Shams Univ., Cairo, Egypt
fYear :
2009
fDate :
21-24 June 2009
Firstpage :
208
Lastpage :
215
Abstract :
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.
Keywords :
brain; image segmentation; medical image processing; expectation maximization; human brain; magnetic resonance images; medical image segmentation; mosaic EM algorithm; multiresolution analysis; spatial resolution; Biomedical imaging; Computer vision; Humans; Image resolution; Image segmentation; Layout; Multiresolution analysis; Signal resolution; Spatial resolution; Wavelet transforms; Expectation Maximization; Information Relevance; Magnetic Resonance Images; Multiresolution; Wavelet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
High Performance Computing & Simulation, 2009. HPCS '09. International Conference on
Conference_Location :
Leipzig
Print_ISBN :
978-1-4244-4906-4
Electronic_ISBN :
978-1-4244-4907-1
Type :
conf
DOI :
10.1109/HPCSIM.2009.5192800
Filename :
5192800
Link To Document :
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