A Content-Based Approach to Image Retrieval in Medical Applications

INTRODUCTION Digital imaging has become the most prominent modality in medicine. Beside computed tomography (CT) or nuclear medicine, which have been always digital, plain radiography, endoscopy, and microscopy are nowadays captured directly digital, too. Picture archiving and communication systems (PACS) have been established in the hospitals all over the world to manage these information resources. PACS are used to store and handle the images, which are transferred based on the digital imaging and communications in medicine (DICOM) protocol. DICOM supports interconnections of PACS modules from different vendors, e.g. for postprocessing of the images and their annotation with alphanumerical attributes such as patient and study information, image descriptions, and diagnostic reports. This textual information, which is stored within the DICOM header, is currently the only means to access and retrieve medical images from the PACS archive. Since an image tells more than a thousand words, recall and precision of this type of medical image information retrieval is limited in general [1,2].