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Detection of Liver Cancer Using Image Processing Techniques

J. Abisha*, B. Kaviya **, A. Naveena ***, N. Saritha ****

*-**** Department of Electronics and Communication Engineering, Jerusalem College of Engineering, Chennai, Tamil Nadu, India.

Periodicity:March - May'2021
DOI : https://doi.org/10.26634/jit.10.2.18220

Abstract

Nowadays, Liver Cancer is spreading silently at an alarming pace since liver disease has a poor survival rate and symptoms do not manifest until cancer has progressed to an advanced stage. If the illness is detected late, the typical individual has only a one-year survival rate. As a result, we propose to diagnose liver cancer via feature extraction and classification. We go through the three detection phases of processing, pre-processing, and detection, then classify the tumours based on the retrieved characteristics for normal and abnormal stages. Three steps comprise the diagnostic method: pre-processing of MRI images, feature extraction, and classification. Following image pre-processing, the picture is segmented using fuzzy C means clustering and a level-set segmenter. Additionally, features are retrieved using the Gray-Level Co-Occurrence Matrix for Texture Analysis (GLCM). Finally, a KNN classifier is used to categorise normal and pathological livers.

Keywords

Liver Cancer, Image Processing, Tumor, KNN, GLCM, Watershed.

How to Cite this Article?

Abisha, J., Kaviya, B., Naveena, A., and Saritha, N. (2021). Detection of Liver Cancer Using Image Processing Techniques. i-manager's Journal on Information Technology, 10(2), 30-41. https://doi.org/10.26634/jit.10.2.18220

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