http://www.iaeme.com/IJCET/index.asp 36 editor@iaeme.com International Journal of Computer Engineering & Technology (IJCET) Volume 8, Issue 3, May-June 2017, pp. 36–55, Article ID: IJCET_08_03_005 Available online at http://www.iaeme.com/ijcet/issues.asp?JType=IJCET&VType=8&IType=3 Journal Impact Factor (2016): 9.3590(Calculated by GISI) www.jifactor.com ISSN Print: 0976-6367 and ISSN Online: 0976–6375 © IAEME Publication REVIEW OF MEDICAL IMAGE SEGMENTATION WITH STATISTICAL APPROACH- STATE OF THE ART AND ANALYSIS Regonda Nagaraju and M. Janga Reddy Research Scholar, SJJT University, Chudela ABSTRACT In recent years, there are many image segmentation algorithms based on level set method have been suggested by the research community in-accordance with the different applications of image processing. At the same time the research communities have put forward the corresponding solutions and continue to improve and enhance the efficiency and effectiveness of these algorithms. In this article, according to the development of the image segmentation methods based on level set, ASM and AAM (statistical methods) overview and analysis is given for readers of different backgrounds in this field to use. These algorithms are summarized from three aspects, i.e., efficiency, discrimination, and robustness. Additionally, some applications and direction for future implementations of SVD based AAM along with level set method is enumerated. The main purpose of this paper is to serve as a guide for further research. Keyword: SVD, AMM, Statistical method, Image processing. Cite this Article: Regonda Nagaraju and M. Janga Reddy, Review of Medical Image Segmentation with Statistical Approach - State of the Art and Analysis. International Journal of Computer Engineering & Technology, 8(2), 2017, pp.36–55. http://www.iaeme.com/ijcet/issues.asp?JType=IJCET&VType=8&IType=3 1. INTRODUCTION Image segmentation is a process of dividing the images into meaningful subsets and always been perceived as one of the most difficult task in the field of image processing and computer vision. The biggest challenge that often encounter during the medical image segmentation is caused due the image noise. In medical imaging, the source of imaging modalities includes CT (Computed Tomography), MRI (Magnetic Resonance Imaging), PET (Positron Emission Tomography) etc. These modalities generate a huge amount of image information useful to rule out the medical related issues. Due to the varying artifacts and quality of the image capturing devices, we not only find the variation in size of the captured images but also changes into the resolution of the images caused due to intensity in homogeneity or non-