Statistical Analysis Of Early Detection Of Liver Cirrhosis

1759 WordsApr 24, 20178 Pages
Statistical Analysis Of Early Detection Of Liver Cirrhosis Through Medical Image Processing Megha Bahdauria1,Chetna Garg1, Dr. Saurabh Mukherjee2, K.F. Rahman2 1.Mtech Scholar, Department of Computer Science, Banasthali University, Rajasthan, India 2. Associate Professor, Department of Computer Science, Banasthali University, Rajasthan, India Abstract: Statistical operations provide the means of principle of solving the many type of problems which require the uncertain information in cirrhosis. This paper discusses the statistical operations. Computed Tomography, Magnetic Resonance Imaging, Ultrasound etc has been proved very helpful in diagnosing liver cirrhosis. Cirrhosis is an endemic disease across the world that leads to observed…show more content…
To let the liver function properly it is important to detect cirrhosis in early stage. Now a days several noninvasive imaging techniques have been developed recently for detection of liver cirrhosis such as CT, USG, MRI. In this paper we have used CT scan images of liver cirrhosis and applied some statistical operations on those CT images such as mean, median, standard deviation and mode. II. Methodology: CT scans are challenging because of the different image characteristics that must be considered. Here we will be considering the statistical features of a CT scan of liver which is having liver cirrhosis as a disease. The methodology followed is given below: Fig.1 Flow Chart of Methodology Used (1).Image Acquisition : To get an image of which you want to extract some features. (2).Image Preprocessing : It is common practice to perform preprocessing on acquired CT scan images before extracting the features of images. Here we have applied the statistical operation on the preprocessed images After acquiring the image various preprocessing methods can be apply. The aim of this step is to improve the quality of the image that suppress unwanted distortion and enhance the image features which is important for further processing. Such as increase or decrease brightness, shape, contrast, remove the noise from the image. (3).Statistical analysis : Image analysis

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