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This paper presents an improved region scalable fitting model that uses fuzzy weighted local features and active contour model for medical image segmentation. Local variance is used with local entropy to extract the regional information from the image which is then processed with the Takagi-Sugeno fuzzy system to compute weights. The use of regional descriptors enables this model to segment the inhomogeneous intensity images. The proposed objective function is minimized by using level setdoaj:2fc68817addc424a8149dd9281f27856 fatcat:qw7h7le5qna55j6hf7lsmljo24