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Medical Image Segmentation Based on Fuzzy Controlled Level Set and Local Statistical
Image segmentation is one of the most important fields in artificial vision due to its complexity and the
diversity of its application to different image cases. In this paper, a new Region of Interest (ROI) segmentation in
medical images approach is proposed, based on modified level sets controlled by fuzzy rules and incorporating
local statistical constraints (mean, variance) in level set evolution function, and low image resolution analysis by
estimating statistical constraints and curvature of curve at low image scale. The image and curve at low resolution
provide information on rough variation of respectively image intensity and curvature value. The weights of
different constraints are controlled and adapted by fuzzy rules which regularize their influence. The objective of
using low resolution image analysis is to avoid stopping the evolution of the level set curve at local maxima or
minima of images. This method is tested on medical images. The obtained results of the technique presented are
satisfying and give a good precision.
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[25] Zadeh L., Fuzzy Sets, Information and Control, vol. 8, no. 3, pp. 338-353, 1965. 816 The International Arab Journal of Information Technology, Vol. 15, No. 5, September 2018 Mohamed Benzian is currently an assistant professor in computer science, at Abou Bekr Belkaid University, Tlemcen, Algeria since 2001. He received his engineering degree in 1993 and his MS Degree in 2001 both from Mohamed Boudiaf University of Science and Technologyof Oran. He is now member of Laboratory SIMPA, at University of Science and Technology, of Oran, Mohamed Boudiaf since 2006. He has published many research papers in national and international conferences His research interests are image processing, 3D reconstruction and modeling. Nac ra Benamrane is currently a full professor and a director of SIMPA laboratory in informatics department at University of Science and Technology of Oran-Mohamed Boudiaf (USTO-MB). She received her engineering degree in Computer Science from University of Oran, the M.Sc. and Ph.D. degrees from University of Valenciennes, France, in 1988 and 1994. Since 2002, she is the head of vision and medical imaging team at SIMPA laboratory. She has published more than 90 papers in journals and conference proceedings. Her main research interests include image processing, medical imaging, computer vision, biomedical engineering and pattern recognition.