Tumor Diagnosis using Gray Level Cooccurrence Matrix and Artificial Neural Network
Different types of tumors diagnosis are a critical responsibility in the direction of estimate the tumors as well as create a cure judgment as per their classes. Different types of imaging ways are utilized to identify brain tumors (BTs). On other hand, Magnetic Resonance Image is frequently used because of its better image quality as well as the reality does not depend on ionizing radiation. Machine Learning (ML) is a sub-field 0f Artificial Intelligence and in recent time demonstrated outstanding performance, particularly in classification as well as segmentation problems. This work based on ML algorithm, an Artificial Neural Network (ANN) is suggested to diagnose a BT. The proposed ANN is a considerable act by using the most excellent general correctness of 94%. The results specify the facility of the ANN form for BT diagnosis intentions.