Machine Learning-Based Active Contour Approach for the Recognition of Brain Tumor Progression

Detection of a tumor in the brain is a quite complex and time-consuming process and early acknowledgment of symptoms can recover the patient’s health timely and also reduces diagnosis cost. The motivation behind this work is to introduce a scheme to classify the disease-related symptoms that are used to track its growth in such a way that practitioners can update the diagnosis strategies for patients. In this chapter, a machine learning approach with an active contour method will be used to examine the growth of brain tumor and its performance will be analyzed using different parameters (i.e. True/False progression/detection ratio, etc.).