Title :
A Bayesian approach for edge detection in medical ultrasound images
Author :
Kao, Chien-Min ; Pan, Xiaochuan ; Hiller, Eric ; Chen, Chin-Tu
Author_Institution :
Dept. of Radiol., Chicago Univ., IL, USA
fDate :
12/1/1998 12:00:00 AM
Abstract :
Successful applications of digital image processing techniques to medical ultrasound images have been limited in part because of the lack of an useful imaging model for clinical ultrasound B-scans. In this work, the authors derive a discrete linear imaging model appropriate for clinical ultrasound B-scans. Based on the newly derived model, the authors developed a Bayesian restoration approach that is currently designed for the generation of correct edges of medical ultrasound images. Their results demonstrate that successful edge detection can indeed be achieved by the proposed method. The proposed Bayesian approach is very flexible and has the potential of being extended to perform speckle reduction, edge detection, and region segmentation at the same time
Keywords :
Bayes methods; biomedical ultrasonics; edge detection; image restoration; image segmentation; medical image processing; modelling; speckle; Bayesian restoration approach; clinical ultrasound B-scans; correct edges generation; medical diagnostic imaging; medical ultrasound images edge detection; region segmentation; speckle reduction; useful imaging model; Adaptive filters; Bayesian methods; Biomedical imaging; Digital images; Filtering; Image edge detection; Image segmentation; Medical diagnostic imaging; Speckle; Ultrasonic imaging;
Journal_Title :
Nuclear Science, IEEE Transactions on