Detection & Classification of Tumor Cells from Bone MR Imagery Using Connected Component Analysis & Neural Network

Bone cancer is a class of diseases that are characterized by an unfettered growth of the cell and it is considered to be the main reasons of early death around the globe. Therefore, early detection and classification of the bone tumor are become needed to cure the patient. This study uses a connected component labeling algorithm for the detection of the bone tumor. In this work, the artificial neural network (ANN) is used for the classification of bone tumor. Total 220 bone MR images of previously verified patients are collected and the texture features of this images are used for the training and testing of the neural network. The obtained performance of the classification result exhibit that the neural network provides 92.50% success rate in bone tumor classification.