On the use of Image Texture in Medical Data Science

Texture features provide statistical, spatial, and structural information of the pixel arrangement of a digital image. A considerable number of new cutting-edge advancements in the medical imaging field involve the usage or application of machine learning and AI techniques, and in many cases, it has been paired with image texture analysis to improve results. We will examine factors that effect the robustness of image texture feature estimations as well as specific features and estimations strategies that would aid segmentation and pattern analysis. Examples will be provided from both simulated and experimental data involving tomographic imaging methods such as partial angle breast tomosyntehsis, computed tomography (CT) and micro CT.