BREAST CANCER DETECTION AND IDENTIFICATION USINGFUZZY C MEANS AND EDGE DETECTION ALGORITHM

Abstract

In recent day’s image processing technique is very exigent and extensively used in medical area for image
amplification, where the time facet is very crucial to discover the anomalous tissues, especially in various cancer such
as Breast Cancer, ovarian cancer, vagina cancer, etc. The growth of cancer cells forwomen is a more aggressive and
harder to treat. Breast cancer is the formation of cancer cell inbreasts.The PET/CT scan is most persistently used
device for diagnosis. In this paper, a well organized algorithm is proposed for Breast cancer, the growth of cancer cells
are detected based on edge detection algorithm and nuclei segmentation of breast from PET/CT scan image using
Fuzzy c means clustering algorithm, the behavior of the cancers patterns of the algorithm are analyzed.The olive color
map function consists of colors that are shades of green and yellow. The edge detection algorithm takes less
computational time than edge detection algorithm and it has the greatest PSNR value than edge detection algorithm.
Finally, edge detected image will be binary image; this image is converted into color image using olive color map
function.