An Approach to Detect and Classify Bone tumour using fast and Robust Fuzzy C Means Clustering technique

Abstract

A tumor is an abnormal growth of new tissue that can occur in any of the body’s organs. There are many kind of tumors detected in the human body like breast cancer, bone tumor, brain tumor, etc . Bone tumors develop when cells within a bone divide uncontrollably, forming a lump or mass of abnormal tissue. Bone marrow biopsy is mostly done to detect any abnormal growth inside the bone. But this procedure carries many risks. Medical image processing is an important field of research as its outcomes are used for the betterment of health issues. This project proposes an approach to detect bone tumor in MRI images. The proposed approach uses fast and robust fuzzy C means clustering (FRFCM) to detect bone tumor from the acquired MRI images. This approach also further identifies whether the tumor is non- cancerous (benign) or cancerous (malignant) based on the comparative analysis of segmentation techniques.