Interpretation of medical images is often difficult and time consuming, even for experienced physicians. The aid of image analysis and machine learning can make this process easier. Assessment of the combined Positron Emission Tomography and Computed Tomography scan images done through multiple modes via the application of image enhancement, morphological operations, noise reduction, segmentation, feature extraction, training and testing of the neural network, can yield various important aspects, properties and attributes of these images, thus spanning the scope of this new medical modality.