Open Access
Subscription Access
Prevalence of Mammography Images for Primal Prediction of Breast Cancer
Breast cancer is the second most common tumour in the world and more common in the women population, not only a women disease its affecting men also, and since the main ischolar_main cause remain unsure, early observation and diagnosis is the best solution to prevent tumour development and allow a successful medical involvement, it’s a lifesavingand the cost reduction. In the absence of symptomsMammography is an x-ray of the breasts performed.Very tiny tumours are identified even before they are real or they are apparent to other symptoms. Mammography is presently the suggested procedure for early identification of Breast Cancer in women in the current scenario it’s an instant require for better pre-screening tool to detect the irregularity of the mammogram resemblance in the early-stage only. The main purpose of this paper is to give a summary current approach in the evolution of breast cancer diagnosis.
Keywords
Breast Cancer, Mammography, Medical Image Processing, Tumor.
User
Font Size
Information
- M. Vasantha, S. Bharathi V and R. Dhamodharan, “Medical image feature, extraction, selection and classification”. Intl. J. Engg.Sci. & Technol. 2(6), 2071-2076, 2010.
- A. Sahar “Predicting the Serverity of Breast Masses with Data Mining Methods” International Journal of Computer Science Issues, Vol. 10, Issues 2, No 2, March 2013 ISSN (Print):1694-0814| ISSN (Online):1694-0784 www.IJCSI.org.
- S. Sondele and I. Saini, "Classification of Mammograms Using Bidimensional Empirical Mode Decomposition Based Features and Artificial Neural Network", International Journal of Bio-Science and BioTechnology, Vol.5, No.6 (2013), pp.171-180.
- Z. K. Senturk and R. “Breast Cancer Diagnosis Via Data Mining: Performance Analysis of Seven Different Algorithms”, Computer Science & Engineering: An International Journal (CSEIJ), Vol. 4, No. 1, February 2014.
- Ismaili, Florije, LuzanaShabani, BujarRaufi, JauminAjdari, and XhemalZenuni. "Enhancing breast cancer detection using data mining classification techniques." PressAcademiaProcedia 5, no. 1 (2017): 310-316.
- Tingting Mu, Asoke K, Nandi, Rangaraj M. Rangayyan, Classification of breast Masses using Selected shapes, edge sharpness, teture features with linear and kernalnased classifies, Journal of Digital Imaging 2008, 21(2)153-169
Abstract Views: 271
PDF Views: 0