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