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Rough-Fuzzy Pattern Recognition: Applications in Bioinformatics and Medical Imaging by Sankar K. Pal, Pradipta Maji

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Chapter 9

Segmentation of Brain Magnetic Resonance Images

9.1 Introduction

Segmentation is a process of partitioning an image space into some nonoverlapping meaningful homogeneous regions. The success of an image analysis system depends on the quality of segmentation [1]. If the domain of the image is given by Ω, then the segmentation problem is to determine the sets Sk ⊂ Ω, whose union is the entire domain Ω. The sets that make up a segmentation must satisfy

9.1 9.1

and each Sk is connected. Hence, a segmentation method is supposed to find those sets that correspond to distinct anatomical structures or regions of interest in the image. In the analysis of medical images for computer-aided diagnosis and therapy, segmentation is often required as a preliminary stage. However, medical image segmentation is a complex and challenging task owing to the intrinsic nature of the images. The brain has a particularly complicated structure and its precise segmentation is very important for detecting tumors, edema, and necrotic tissues, in order to prescribe appropriate therapy [2].

In medical imaging technology, a number of complementary diagnostic tools such as X-ray computer tomography, magnetic resonance imaging (MRI), and positron emission tomography are available. The MRI is an important diagnostic imaging technique for the early detection of abnormal changes in tissues and organs. Its unique ...

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