Breast Tissue

Breast tissue research focuses on improving the accuracy and efficiency of breast cancer detection and diagnosis, primarily through advanced image analysis techniques. Current research heavily utilizes deep learning models, including convolutional neural networks (CNNs) like EfficientNet and ResNet, and novel architectures like the Segment Anything Model (SAM), often coupled with federated learning to address data privacy and heterogeneity across datasets. These efforts aim to improve the speed and accuracy of diagnosis, potentially leading to earlier interventions and better patient outcomes, and are facilitated by the increasing availability of large, publicly accessible datasets of breast imaging data.