Automatic contour retrieval in annotated TRUS prostate images

The approach proposed in this paper retrieves contours from transrectal ultrasound (TRUS) prostate images. The input images are sparsely annotated by radiologists for the purpose of brachytherapy planning and post-interventional. monitoring. The theoretical contribution of the paper consists in the design of a task-oriented, bottom-up method which mimics perceptual grouping mechanisms for contour retrieval. The proposed approach is task-oriented because it embeds prior anatomical and procedural knowledge. From a practical standpoint, the proposed approach is of clinical relevance, since it allows for retrieving contours from images where the annotation is 'blended' with the image content. While new image annotation systems are able to store image content and annotations in a separate manner, many TRUS prostate databases still contain 'blended' annotations only. Our approach allows for contour retrieval and further 3D prostate modeling from such databases.