Medical Object Detection

Medical object detection uses computer vision to automatically identify and locate anatomical structures, lesions, or other objects within medical images and videos. Current research emphasizes improving the accuracy and efficiency of detection, particularly for small or subtle features, often employing architectures like YOLO and transformers, and addressing challenges like imbalanced datasets and noisy labels through techniques such as active learning and self-supervised pretraining. These advancements hold significant potential for improving diagnostic accuracy, streamlining workflows, and assisting clinicians in various medical specialties.