Title :
A Bayesian approach for edge extraction in ultrasound images and its application to image segmentation
Author :
Kao, Chie-Min ; Pan, Xiaochuan ; Hiller, Eric ; Chen, Chin-Tu
Author_Institution :
Dept. of Radiol., Chicago Univ., IL, USA
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 which is currently designed for the generation of correct edges of medical ultrasound images. The results demonstrate that successful edge detection can indeed be achieved by the proposed method
Keywords :
Bayes methods; biomedical ultrasonics; edge detection; image restoration; image segmentation; medical image processing; modelling; Bayesian restoration approach; clinical ultrasound B-scans; correct edges generation; discrete linear imaging model; imaging model; medical diagnostic imaging; medical ultrasound images; successful edge detection; ultrasound images edge extraction; Bayesian methods; Biomedical imaging; Digital images; Image edge detection; Image resolution; Image restoration; Image segmentation; Medical diagnostic imaging; Speckle; Ultrasonic imaging;
Conference_Titel :
Nuclear Science Symposium, 1997. IEEE
Conference_Location :
Albuquerque, NM
Print_ISBN :
0-7803-4258-5
DOI :
10.1109/NSSMIC.1997.670598