Magnetic Resonance Imaging (MRI) is one of the most used imaging modalities for the identification and quantification of various types of cancers. MRI image analysis is mostly conducted by experts relying on the visual interpretation of the images and some basic semiquantitative parameters. However, it is well known that additional clinical information is available in these images and can be harvested using the field of radiomics. This consists of the extraction of complex unexplored features from these images that can provide underlying functions in disease process. In this paper, we provide a review of the application of radiomics to extract relevant information from MRI Diffusion Weighted Imaging (DWI) for the classification of cervix cancer. The main research findings are the presentation of the state of the art of this application with the description of its main steps and related challenges.