Multiple instance learning algorithm for medical image classification

After an overview on most relevant methods for image classification, we focus on a recently proposed Multiple Instance Learning (MIL) approach, suitable for image processing applications and based on a mixed integer nonlinear optimization problem. In particular, the algorithm has been preliminarily applied to a set of color images, with the aim to identify images containing some specific color pattern, and successively to a medical dataset, containing photos of melanoma and common nevi. Since the results appear promising, this technique could be at the basis of computer vision systems that act as a filter mechanism to support physicians in detecting melanomas cancer.