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Research Journal of Pharmacy and Technology
Year : 2018, Volume : 11, Issue : 2
First page : ( 434) Last page : ( 438)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2018.00080.X

MRI Liver Tumor Classification Using Machine Learning Approach and Structure Analysis

Devi Shyamala M*, Sruthi A. N, Jothi Saranya C

Associate Professor, Assistant Professor, Department of Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Saguntahala R and D Institute of Science and Technology, Avadi, Chennai, Tamil Nadu, India

*Corresponding Author E-mail: shyamalapmr@gmail.com

Online published on 12 June, 2018.

Abstract

The survival rate of Liver tumor patients can be improved if we perform early detection and treating them. The clinical researches have exposed that the volume measurement can give the best reflection of the tumor response. The liver tumor requires the tumor segmentation. This paper proposes an automatic support system for stage classification using artificial neural network (learning machine) and to detect Liver Tumor through fuzzy clustering methods for medical application. The detection of the Liver Tumor is a challenging problem, due to the structure of the Tumor cells. This project presents a segmentation method, fuzzy clustering algorithm, for segmenting Magnetic Resonance images to detect the Liver Tumor in its early stages and to analyze anatomical structures.

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Keywords

Liver Tumor, ANN, Segmentation, Fuzzy Clustering, Resonance Image.

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