DocumentCode :
3418216
Title :
Mass detection based on integrated region growing and level set method
Author :
Liu, Jun ; Chen, Jianxun ; Liu, Xiaoming ; Tang, J.
Author_Institution :
Coll. of Comput. Sci. & Technol., Wuhan Univ. of Sci. & Technol., Wuhan, China
fYear :
2011
fDate :
19-21 Oct. 2011
Firstpage :
557
Lastpage :
560
Abstract :
In this paper, an automatically method for mass detection was introduced, which combines multiple layers concentric (MLC) and narrow band region-based active contour (NBAC) technique. We used an improved level set method to segment the mass for contour refinement, after the boundary of a mass is found, texture features from Gray Level Cooccurrence Matrix (GLCM) are extracted from the surrounding area of the boundary of the mass. The extracted texture features are used to reduce the false positive. Mammography images from DDSM were used in the experiments and the method was evaluated, it obtained 1.38 FPsI at the sensitivity 79.3%. The result shows the effectiveness of the proposed method.
Keywords :
cancer; feature extraction; image segmentation; image texture; mammography; medical image processing; object detection; 1.38 FPsI; DDSM; Gray level cooccurrence matrix; automatic mass detection method; contour refinement; integrated region growth; level set method; mammography images; mass segmentation; multiple layer concentric technique; narrow band region based active contour technique; texture feature extraction; Active contours; Cancer; Feature extraction; Image segmentation; Level set; Sensitivity; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computational Intelligence (IWACI), 2011 Fourth International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-61284-374-2
Type :
conf
DOI :
10.1109/IWACI.2011.6160071
Filename :
6160071
Link To Document :
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