چکیده مقاله
Breast cancer is the most common cancer among women and the earlier breast cancer is diagnosed, the easier it is to treat The most common way to diagnose breast cancer is mammography Mammography is a simple x ray image of the breast and a tool for early detection of cancers and non palpable breast tumors However, due to some limitations of this method such as low sensitivity especially in dense breasts, other methods such as 3D mammography, ultrasound and magnetic resonance imaging are often suggested to obtain more and more accurate information Recently, computer aided or intelligent diagnosis systems have been developed to assist radiologists in increasing diagnostic accuracy In general, a computer system consists of four steps: preprocessing, dividing regions of interest ROI , extracting and selecting features, and finally classification Today, the use of image processing methods and techniques and pattern recognition in the automatic diagnosis and determination of breast cancer from mammography images and even digital pathology, which is one of the emerging trends in modern medicine, reduce human errors and increase the speed of diagnosis In this review article, the work done and its advantages and disadvantages in the field of breast cancer diagnosis with the help of neural networks, especially the convolutional artificial neural network, which has been widely used in the diagnosis of all types of cancers, especially the intelligent diagnosis of breast cancer, is discussed has been Review of articles shows that hybrid algorithms have been better in improving classification and detection accuracy
کلیدواژهها
نویسندگان
Rezvan Rashidifard
Bachelor of cell Molecular Genetics University Hamadan
شیوه ارجاع
Rashidifard, Rezvan,1402,Breast cancer diagnosis based on neural networks,The 11th International Conference on New Findings in Obstetrics, Women, Childbirth and Infertility
ارائهشده در
مجموعه مقالات یازدهمین کنفرانس بین المللی یافته های نو در مامایی، زنان، زایمان و نازایی19 آبان 1402