The main objective of any diagnostic study of image is the characterization of tissues. Therefore images are acquired in order to determine whether the tissues in the selected area for study show normal (healthy tissue) or pathological characteristics. Hence, giving the exact appearance of the tissue in the image, pathology is classified in the most precise way possible, by refering to other diagnostic data. This process requires both a complex evaluation of the various properties which characterize the appearance of the image studied and the comparison of these properties with the radiologist's experimental database. Giving the subjective nature inherent in the majority of appreciations associated with this process, the expert is able to accomplish this task with precision and exactitude. There does however exist a significant series of diagnostic problems, for which simple visual analysis of the image is insufficient for the specific pathologic characterization of tissues. It was this clinical requirement which encouraged scientists to develop advanced methodologies concerning both acquisition systems and image processing methods. As a starting point, researchers naturally considered the image characteristics that radiologists use explicitly or implicitly in their evaluation of tissue appearance. Intensity, morphology and texture are usually quoted as important characteristics. Image texture is known to be a particularly sensitive characteristic in the evaluation of pathologies. Its visual analysis has always been used in medical imaging in order to establish a diagnosis. It is however well known that the human observer has only a limited sensitivity to textural properties, whereas mathematical techniques for texture analysis give quantitative and therefore objective elements. It is for this reason that many studies have been carried out in the aim of automating this analysis. This chapter is composed of an introduction, a conclusion and three parts : part two outlines the main methods of texture analysis in the medical field, part three summarizes the medical applications which use these techniques and part four describes several experiments in greater detail.