System and methods for machine learning based trackingless volume reconstruction
RPI presents a novel, DCL-Net system, and method based on a machine learning/DL technique to reconstruct 3D volumes from a series of 2D images. The developed technology does not require the use of sensor tracking hardware/devices (e.g., robotic arms, touchless position/pose trackers) to operate. The technology acquires multiple (two or more) consecutive, 2D US-generated image frames using a handheld imaging sensor or a sensor mounted on a motion restricted device used as inputs for estimating a US probe trajectory and tracking its motion.