Early detection of breast cancer through medical imaging

Joint Event on 5^th International Conference on Artificial Intelligence & 5^th International Conference on Automation & Robotics

April 16-17, 2018 | Las Vegas, USA

Sehreen Moorat

Liaquat University of Medical Health and Sciences, Pakistan

Posters & Accepted Abstracts: Adv Robot Autom

Abstract :

Breast cancer is the main cause of death among women in world. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is an effective method which detects the cancer before it is felt and increases the survival rate. In this thesis, we purposed image processing technique for enhancing the image, from enhanced images ROI has been detected based on GT data and markings. Texture features based on GLCM and intensity based features are extracted from the ROI. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer. sehreen.moorat@lumhs.edu.pk