Semi - Automatic Segmentation of Human Breast from Thermal Images for Analysis of Human Breast Cancer
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 2 | Views: 392 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1

Masters Thesis | Biomedical Sciences | India | Volume 11 Issue 6, June 2022 | Popularity: 4.5 / 10


     

Semi - Automatic Segmentation of Human Breast from Thermal Images for Analysis of Human Breast Cancer

A. R. Shwethaa, Divyashree .K


Abstract: Breast cancer is a dreadful disease in woman and it is very common between the age group of 25 - 40, above 40 it becomes more malignant and also difficult to diagnose as it spreads at a faster rate and it cannot be treated. Infrared Thermography (IR) is preferred as one such technique for diagnosis, as it has the ability to detect the temperature variations which differentiates between hot spots and cold spots. The hot spots are likely to be the cancer area. This paper proposes a technique for segmentation of breasts into left and right respectively. An infrared image is taken and the breast segmentation is carried out semi - automatically. Segmentation is a crucial step for analysis purposes. The original contribution of this work is to separate the breast by segmentation and thresholding techniques for further analysis.


Keywords: Image Processing, Thermography, Semi - Automatic Segmentation


Edition: Volume 11 Issue 6, June 2022


Pages: 1769 - 1772


DOI: https://www.doi.org/10.21275/SR22619232957


Please Disable the Pop-Up Blocker of Web Browser

Verification Code will appear in 2 Seconds ... Wait





Text copied to Clipboard!
A. R. Shwethaa, Divyashree .K, "Semi - Automatic Segmentation of Human Breast from Thermal Images for Analysis of Human Breast Cancer", International Journal of Science and Research (IJSR), Volume 11 Issue 6, June 2022, pp. 1769-1772, https://www.ijsr.net/getabstract.php?paperid=SR22619232957, DOI: https://www.doi.org/10.21275/SR22619232957

Top