DocumentCode :
2422001
Title :
Extracting boundaries of ultrasonic breast tumor images based on a coarse-to-fine active contour model
Author :
Yang, Xiaoshuang ; Wang, Yuanyuan
Author_Institution :
Dept. of Electron. Eng., Fudan Univ., Shanghai
fYear :
2008
fDate :
7-9 July 2008
Firstpage :
157
Lastpage :
162
Abstract :
Segmentation of ultrasonic breast tumor images is a challenging topic in the clinical practice. A novel coarse-to-fine active contour (CFAC) model is proposed to extract boundaries of breast tumors based on a level-set framework. To apply the CFAC model, a Gaussian pyramid is firstly constructed to represent images at different resolution levels. Then, on the top pyramid level a region-based segmentation algorithm incorporating with the certain edge information is used to get a coarse boundary. Finally, the coarse boundary is gradually refined on other higher-level images according to the more detailed gradient information. Experiments are performed on both synthetic and real ultrasonic breast tumor images. The qualitative and quantitative results verified the efficiency of the CFAC model for the image segmentation task.
Keywords :
Gaussian processes; biomedical ultrasonics; edge detection; feature extraction; image representation; image resolution; image segmentation; medical image processing; tumours; Gaussian pyramid; coarse-to-fine active contour model; edge information; gradient information; image representation; image resolution; image segmentation; level-set framework; region-based segmentation; ultrasonic breast tumor image boundary extraction; Active contours; Biomedical imaging; Breast neoplasms; Breast tumors; Data mining; Dynamic range; Image resolution; Image segmentation; Shape; Ultrasonic imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Audio, Language and Image Processing, 2008. ICALIP 2008. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1723-0
Electronic_ISBN :
978-1-4244-1724-7
Type :
conf
DOI :
10.1109/ICALIP.2008.4589959
Filename :
4589959
Link To Document :
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