Processed images in human perception: A case study in ultrasound breast imaging

Abstract

Two main research efforts in early detection of breast cancer include the development of software tools to assist radiologists in identifying abnormalities and the development of training tools to enhance their skills. Medical image analysis systems, widely known as Computer-Aided Diagnosis (CADx) systems, play an important role in this respect. Often it is important to determine whether there is a benefit in including computer-processed images in the development of such software tools. In this paper, we investigate the effects of computer-processed images in improving human performance in ultrasound breast cancer detection (a perceptual task) and classification (a cognitive task). A survey was conducted on a group of expert radiologists and a group of non-radiologists. In our experiments, random test images from a large database of ultrasound images were presented to subjects. In order to gather appropriate formal feedback, questionnaires were prepared to comment on random selections of original images only, and on image pairs consisting of original images displayed alongside computer-processed images. We critically compare and contrast the performance of the two groups according to perceptual and cognitive tasks. From a Receiver Operating Curve (ROC) analysis, we conclude that the provision of computer-processed images alongside the original ultrasound images, significantly improve the perceptual tasks of non-radiologists but only marginal improvements are shown in the perceptual and cognitive tasks of the group of expert radiologists.