Ultrasound Image
Ultrasound image analysis focuses on extracting meaningful information from ultrasound scans for medical diagnosis and treatment. Current research emphasizes developing robust deep learning models, including convolutional neural networks (CNNs), transformers, and generative adversarial networks (GANs), often combined in hybrid architectures, to improve image segmentation, classification, and noise reduction. These advancements aim to enhance diagnostic accuracy, particularly in areas with limited expert access, and facilitate automated tasks like lesion detection and report generation, ultimately improving patient care and workflow efficiency. The field is also actively exploring explainable AI (XAI) techniques to increase the transparency and trustworthiness of these powerful algorithms.
Papers
Enhanced Breast Cancer Tumor Classification using MobileNetV2: A Detailed Exploration on Image Intensity, Error Mitigation, and Streamlit-driven Real-time Deployment
Aaditya Surya, Aditya Shah, Jarnell Kabore, Subash Sasikumar
Breast Ultrasound Report Generation using LangChain
Jaeyoung Huh, Hyun Jeong Park, Jong Chul Ye