ABSTRACT
Image mining is a critical method for direct knowledge mining from image after image processing. It is an interdisciplinary domain that incorporates several methods such as computer vision, image processing, data mining, machine learning, artificial intelligence, and database. In addition, in image mining, segmentation is considered to be the main stage. Image mining is employed in hidden information extraction, image data association, and supplementary patterns that are not collected in the images. The most significant mining purpose is the generation of all relevant patterns without previous knowledge about those patterns. Mining is done along with the combined images groups and their associated data. The current work introduces the image mining concept in the medical domain. It presents a survey on several image segmentation methods that were suggested in earlier studies. The medical image mining for computer-aided diagnosis is discussed. Furthermore, the machine learning–based segmentation for medical image mining is depicted. Several related applications as well as the challenges and the future perspective are also illustrated.
