Title :
Image decomposition based ultrasound image segmentation by using fuzzy clustering
Author_Institution :
Coll. of Comput. Sci., Sichuan Univ., Chengdu, China
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 image decomposition. First, an ultrasound image is decomposed into a sum of two functions, u+v, where u denotes the image intensity while v refers to the texture. And then, a spatial FCM clustering method is applied on the image intensity component for segmentation. In the experiments with simulated and clinical ultrasound images, the proposed method can get more accurate results than other preprocessing or segmentation methods.
Keywords :
fuzzy set theory; image segmentation; image texture; medical image processing; pattern clustering; speckle; ultrasonic imaging; boundaries fuzziness; fuzzy c-means clustering; fuzzy clustering; image decomposition; image intensity; image texture; speckle noise; ultrasound image segmentation; Data mining; Filtering; Image decomposition; Image segmentation; Industrial electronics; Noise reduction; Pixel; Speckle; Ultrasonic imaging; Wiener filter; Decomposition; Fuzzy Clustering; Segmentation; Ultrasound;
Conference_Titel :
Industrial Electronics & Applications, 2009. ISIEA 2009. IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-4681-0
Electronic_ISBN :
978-1-4244-4683-4
DOI :
10.1109/ISIEA.2009.5356492