DocumentCode :
228625
Title :
Analysis of Ductal carcinoma using K-means clustering
Author :
Vijayaraghavan, R. ; Eswari, C. ; Raajan, N.R.
Author_Institution :
Dept. of Electron. & Commun. Eng., SASTRA Univ., Thanjavur, India
fYear :
2014
fDate :
13-14 Feb. 2014
Firstpage :
1
Lastpage :
4
Abstract :
Cancer that emerging in tissues of breast is a breast cancer. Breast cancer has mainly stemmed from the lining of the milk ducts or lobules. The vast preponderance of breast cancer ailment appears in women than in men. There were approximately 13,668 deaths from breast cancer diagnosed in women as per surveyed in 2009, it will be expected that there will be 17,210 breast cancer deaths in 2020. The earliest method of examining the breast cancer is mammography by using the low range of X-rays. Hereby, we are using the K-means clustering to segment the affected area of the breast cancer by applying the image processing techniques. It is mainly used for cluster analysis in medical field. According to their characteristics, pixels are grouped and then precisely determine the affected area.
Keywords :
biological tissues; cancer; diagnostic radiography; image segmentation; mammography; medical image processing; K-means clustering; X-rays; breast cancer area segmentation; breast cancer diagnosis; breast tissues; ductal carcinoma analysis; image processing techniques; mammography; milk ducts; milk lobules; Educational institutions; Frequency estimation; Frequency-domain analysis; Image segmentation; Indexes; Microscopy; X-rays; Breast cancer; K-mean clustering algorithm; Lobules; Mammogram; segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics and Communication Systems (ICECS), 2014 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-2321-2
Type :
conf
DOI :
10.1109/ECS.2014.6892704
Filename :
6892704
Link To Document :
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