Bias Field Correction and Image Segmentation in MRI

. Segmentation of brain MR images into types of tissues is an important job for automatic image analysis technique. In medical images the Bias field estimation and classification is an important task for image processing and analysis. In this paper a new incorporated classification and bias field analysis of Magnetic Resonance Image (MRI) of brain is present, which simultaneously segments and estimates the bias field and removes the noise in MRI with the same Energy model. The Rough Set Theory defines total coherent local intensity clustering phenomena function for solving the problem with membership function. The proposed method defines with comparison and evolution is done with Fuzzy C Means (FCM), Modified Fuzzy C Means (MFCM) and Multiplicative Intrinsic Component Optimization (MICO). The performance evolution is done in terms of Jccard Similarity Index (JSI) and Timing taken analysis. The proposed method shows better time taken compare with existing algorithms.