DocumentCode :
3130899
Title :
Textural Feature Analysis for Ultrasound Breast Tumor Images
Author :
Chen, Qiuxia ; Liu, Qi
Author_Institution :
Dept. of Med. Inf. Eng., Sichuan Univ., Chengdu, China
fYear :
2010
fDate :
18-20 June 2010
Firstpage :
1
Lastpage :
4
Abstract :
Texture is one of the important characteristics used in identifying objects or regions of interest in an image. This paper describes some textural features based on integrated spatial gray level co-occurrence matrix, and illustrates the effectiveness of four textural features in categorizing ultrasound breast tumor images by means of Fuzzy C-means and K-medoid clustering algorithms respectively. The experimental identification accuracy is 72.6415 percent. These results indicate that textural features probably have a general applicability for classification of breast tumors.
Keywords :
biological organs; biomedical ultrasonics; fuzzy systems; gynaecology; image classification; image texture; medical image processing; pattern clustering; tumours; Fuzzy C-means; K-medoid clustering algorithms; integrated spatial gray level; textural feature analysis; ultrasound breast tumor images; Biomedical imaging; Breast tumors; Cancer; Clustering algorithms; Clustering methods; Image analysis; Image segmentation; Image texture analysis; Information analysis; Ultrasonic imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on
Conference_Location :
Chengdu
ISSN :
2151-7614
Print_ISBN :
978-1-4244-4712-1
Electronic_ISBN :
2151-7614
Type :
conf
DOI :
10.1109/ICBBE.2010.5516918
Filename :
5516918
Link To Document :
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