Early detection of Cancer using Mammograms with Advanced Artificial Intelligence (AI) Algorithms for Breast lesions

Background: Breast cancer is the second most common cancer and leading cause of cancer death among women worldwide. Objective: To early detect breast cancer by application of computerized methods on mammography images. Methods: This study is based on the computerized detection of lesions on mammograms which was conducted at the Radiation Therapy Unit, AIMC/Jinnah Hospital Lahore during 2021-22. A total of 322 cases from the Image Processing Archive (PEIPA) MIAS database were retrieved. The case can be described by seven attributes. The attributes include the MIAS database reference number, the type of background tissue (F-fatty, G-fatty-glandular, or D-Dense-glandular), and more. Results: Accuracy is calculated to check the performance of the method. Our algorithm produced good results with an accuracy of 98.12 % in the detection of cancer regions in images. The accuracy achieved for benign cases is 96.1% and for normal cases is 98.2% respectively. Conclusion: Based on this method, a tool for improved breast cancer detection can be created