DEEP LEARNING BASED BREAST CANCER DETECTION USING ULTRASOUND IMAGE

Abstract

In the fields of healthcare and bioinformatics, the definition of breast cancer has been the topic of concern, since this is the second principal explanation for death from cancer in women. This form of study will only be achieved if a sample of breast tissue is extracted from the breast, evaluated, and analyzed under a microscope. In the histopathology lab, problems are detected by examining the specimens using trained and qualified pathologists, and identified with further investigation using special techniques. However, the ultrasound can incorrectly identify pathological changes or conditions because they have practiced in this specialty before. Several pattern recognition studies have recently identified a lot of areas for potential for improvement, and, hence there is now an increased focus on constructing powerful image processing experiments to create a highly-and improving existing diagnoses. Let’s use the histology and image recognition techniques to identify the disease types of breast through the use of the image feature extraction technique and deep learning approaches for the image feature. This picture can be expanded using ultrasound processing and CNN technique is available before ultrasound feature extraction is applied and the final classification in ultrasound feature extraction.