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