Title :
A modified spatial fuzzy clustering method based on texture analysis for ultrasound image segmentation
Author_Institution :
Grad. Sch. of Inf., Production & Syst., Waseda Univ., Kitakyushu, Japan
Abstract :
Ultrasound image segmentation is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, we propose a segmentation scheme using fuzzy c-means (FCM) clustering incorporating spatial information based on intensity and texture of images. Firstly, the nonlinear structure tensor, which helps to refine the edges detected by intensity, is used to extract speckle texture. And then, a spatial FCM clustering method is applied on the image feature space for segmentation. In the experiments with simulated and clinical ultrasound images, the proposed method can get more accurate results than the conventional FCM and other segmentation methods.
Keywords :
biomedical ultrasonics; edge detection; fuzzy set theory; image segmentation; image texture; medical image processing; pattern clustering; ultrasonic imaging; edge detection; nonlinear structure tensor; spatial fuzzy c-means clustering; speckle noise; texture analysis; ultrasound image segmentation; Clustering methods; Data mining; Image analysis; Image edge detection; Image segmentation; Image texture analysis; Interference; Speckle; Tensile stress; Ultrasonic imaging;
Conference_Titel :
Industrial Electronics, 2009. ISIE 2009. IEEE International Symposium on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-4347-5
Electronic_ISBN :
978-1-4244-4349-9
DOI :
10.1109/ISIE.2009.5213933