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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Breast cancer is the most common cancer among women. Our paper mainly focuses on classification of breast masses with the Triangular Area Representation (TAR) signatures. Breast masses are characterized by its gray level values and shape complexity. So, shape descriptors are calculated from the TAR signature of mass contours and given to different classifiers for the classification of benign and malignant contours .We tested our proposed method on 148 mass contours which are taken from DDSM mammogram database. Out of the total images used for evaluation 74 images were malignant and other 74 images were benign. The proposed method attained accuracy of 90.9% and 0.95 AUC (Area Under Curve) value with SVM (support vector machine) classifier

Application of TAR signature for breast mass analysis