Patient Positioning

Precise patient positioning is crucial for accurate medical procedures, particularly in radiotherapy and imaging, where even small errors can compromise treatment efficacy or diagnostic accuracy. Current research focuses on developing automated systems using various techniques, including 3D image reconstruction from 2D projections, hand gesture recognition for automated adjustments, and self-supervised learning for 3D patient modeling from multimodal data, often employing convolutional neural networks and vision transformers. These advancements aim to improve positioning accuracy, reduce procedural time, minimize radiation exposure, and ultimately enhance patient care and treatment outcomes.