English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Mammography is an efficient and contemporary option in diagnosing breast cancer among all ages of women. Nevertheless, the radiologist's has remarkable influence on revelation of the mammogram. It is a difficult and challenging task in identifying the masses in the breast region of a digital mammography. The proposed research intends to develop an image processing algorithm in identifying malignancy by using an automated segmentation technique for mammogram. The proposed work deals with an approach for extracting the malignant masses in mammograms for detection of breast cancer. The work proposed is based on the following procedure: (a)Removing the noise and the background information. (b)Applying thresholding and retrieving the largest region of interest (ROI). (c)Performing the morphological operations and extracting the ROI and identifying the malignant mass from the screened images of the breast. This method was tested over several images of various patients taken from a cancer hospital and implemented using Matlab code. Thus, capable in executing the pre-processed image effectively and detected the segmentation region and identified the malignant data for assessment.

Detection of Malignancy in Digital Mammograms from Segmented Breast Region Using Morphological Techniques