Ultrasound Image-Based Breast Cancer Detection

Abstract

Breast cancer is the second most common cause of cancer-related death in women, the definition of breast cancer has drawn attention from the bioinformatics and healthcare communities. Only by removing a sample of breast tissue from the breast, examining, and analyzing it under a microscope would this type of research be possible. In the histopathology lab, issues are found by employing skilled pathologists to examine the specimens; these issues are then further investigated utilizing specialized procedures. However, because they have experience in this field, the ultrasonography may mistakenly reveal abnormal changes or diseases. Recent pattern recognition research has revealed several areas that could be improved, therefore there is now more of an emphasis on building strong image processing experiments to provide a highly-and enhancing current diagnosis. Let's employ deep learning approaches for the image feature and the image feature extraction methodology to detect the disease types of breast tissue using histology and image recognition techniques. Before using ultrasonic feature extraction and the final classification in ultrasound feature extraction, this image can be enlarged utilizing ultrasound processing and CNN approach. Index Terms— Machine learning algorithm, Ultra sound image, MRI.