Ultrasound Image Analysis for Breast Cancer Detection and Prognosis Prediction Using DL

Breast cancer still claims thousands of lives each year. Early detection? It’s a lifesaver, period. We’ve created a two-component system that processes ultrasound images and, at the same time, processes clinical information to not only identify cancerous tissues, but to also determine potential progression. Here’s the process: Component one uses a VGG19 neural network to scan ultrasound images of the breasts, separating them into normal tissues, benign, and cancerous tissues. Component two processes clinical data, including the patient’s age, tumor type, and medical history, to determine the potential aggressiveness and progression of the cancer through machine learning. It all happens through a web app interface. Python supports the calculations. Meanwhile, the interface itself uses HTML and CSS. We get a system that integrates image analysis and data analysis for clinical purposes, not requiring expertise to operate and interpret results.