Bone Cancer Detection using Artificial Neural Network

Numerous people lose their lives to a terrible illness called bone cancer. In order to detect cancer at an early stage, the detection and classification system must be accessible. The patient's likelihood of survival when suffering from cancer appears to be only increased by early identification. Among the most difficult challenges in clinical diagnosis is the classification of cancer. This study focuses on a system that analyses magnetic resonance imaging (MRI) of various individuals to identify tumors and categories cancer using artificial neural networks. The suggested methodology employs preprocessing methods like filtering and grey conversion, as well as image processing methods like edge detection, morphological operation, segmentation, feature extraction, and classification, to identify bone cancer. The proposed approach will significantly speed up the process needed for cancer detection and classification.

Keywords: bone cancer, preprocessing techniques, segmentation, feature extraction, artificial neural network.