Assessment on Liver Disease Classification using Medical Image Processing
A. Bathsheba Parimala1, R. S. Shanmugasundaram2
1A. Bathsheba Parimala*, Research Scholar, Department of Computer Science, Vinayaka Mission’s Research Foundation, (Deemed to be University), Salem, Tamilnadu, India.
2Dr. R. S. Shanmugasundaram, Professor, Department of Computer Science, Vinayaka Mission’s Research Foundation, (Deemed to be University), Salem, Tamilnadu, India.
Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 4167-4181 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6217018520/2020©BEIESP | DOI: 10.35940/ijrte.E6217.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Chronic hepatic disease (CHD) is progressive fatal disease which is often asymptomatic. CHD has increased mortality and morbidity rate even in developed countries also. Invasive and non-invasive methods are used to classify and stage the CHD. In the research, using Ultra Sonographic images (US), clinical finding and laboratory findings for the staging of CHD is done. There are three stages of CHD which are Chronic Hepatitis, Compensated Cirrhosis and Decompensated cirrhosis. For invasive method, liver biopsy is done followed by histopathological examinations. Results of liver biopsy have some complications. So, non-invasive procedures are used as a safe alternative for liver biopsy. This paper presents current various methods of segmentation based on medical liver images. And also, this paper focuses on the work of various segmentation and classification methods that has been proposed to diagnosis many liver diseases.
Keywords: Chronic Hepatic Disease, Computer Aided Diagnosis, Image Processing, Medical Image Processing, Non-invasive method.
Scope of the Article: Digital Signal Processing Theory.