Detection, Identification and Tracking of Anomaly in Medical Images

In this work, we will develop an algorithm based on unsupervised region segmentation for the detection, identification and traking of anomalies in a set of medical images. We created an algorithmic system based on k-means segmentation to identify cancerous regions and track the progression of infected people. Several experiments were carried out based on images to guarantee the reliability of our software tool. The results are satisfactory and robust for aiding medical diagnosis.