Imaging Protocol

Medical imaging protocol research focuses on improving image acquisition, processing, and analysis to enhance diagnostic accuracy and efficiency. Current efforts leverage deep learning, particularly convolutional neural networks and generative adversarial networks (GANs), to address challenges such as limited data, artifact reduction (e.g., in sparse-view CT), and image super-resolution. These advancements aim to improve the detection of subtle pathologies, optimize workflow (e.g., through automated anatomical localization), and ultimately contribute to more precise and timely diagnoses across various imaging modalities.