Development and Validation of Brain Metastasis Detection System using Artificial Neural Network on MR

Brain tumor detection and segmentation in magnetic resonance images is important in medical diagnosis because it provides information associated to anatomical structures as well as potential abnormal tissues necessary to treatment planning and patient follow-up. In this research, we proposed the fully automated brain metastasis detection system. We performed normalization and brain region extraction in preprocessing. We developed a CAD system for brain metastasis detection using template matching and K-means clustering algorithms for candidate detection, and artificial neural network for false-positive reduction. The proposed method showed a sensitivity of 87.3% (117/134 nodules). In the future, we expected that further research would improve the performance of the proposed method.