Efficient Bone Tumor Detection and Classification using Fuzzy C Means Clustering Algorithm

Abstract

An irregular development of a suspicious tissue that may appear in all of the organs of the human body is a tumour. Inside the human body, there are several types of tumours found, such as breast cancer, bone cancer, brain tumour, etc. Bone tumours form when some cells inside a bone divide enormously, ending in a mound of irregular group of cells. Bone marrow biopsy is often performed to detect any abnormal development within the bone. The analysis of medical images is an important area of study as its findings are used to strengthen health problems. This project states a way to find tumor in bone using MRI images. To locate bone tumors from acquired MRI images, the proposed method employs Fast and Robust Fuzzy C Means Clustering (FRFCM). This approach also further identifies whether the tumor is non-cancerous (benign) or cancerous (malignant) based on the comparative analysis of segmentation technique.