Medical Image Processing: A Challenging Analysis

Abstract

Medical image processing is an multifaceted field at the intersection of computer science, electrical engineering, physics, mathematics and medicine. Medical Image processing has developed versatile computational and mathematical methods for solving problems pertaining to medical images and their use for biomedical research and clinical care. The prominent and important motive of Medical Image Processing is to extract clinically relevant information or knowledge from medical images. MIP focuses on the computational analysis of the images, not their acquisition. The methods can be grouped categorized as: image segmentation, image registration, image-based physiological modeling, Research in Medical Image Processing (MIP) is mainly driven by a technology oriented point of view. MIP research should always be able to give an answer to the question of what is the potential benefit of a solved MIP problem or a newly developed MIP-based system supporting a diagnostic or therapeutic process, in terms of outcome criteria like, e.g., Quality Adjusted Life Years (QALYs) for the patient or cost savings in health care. This paper presents the concept and the strategy of how the Most Relevant MIP problems (MRMIP) shall be identified and assessed in the context of improving evaluation of MIP solutions.