Abstract: Disclosed is a medical imaging conversion method, automatically converting: at least one or more real x-ray images of a patient, including at least a first anatomical structure of the patient and a second anatomical structure of the patient, into at least one digitally reconstructed radiograph (DRR) of the patient representing the first anatomical structure without representing the second anatomical structure, by a single operation using either one convolutional neural network (CNN) or a group of convolutional neural networks (CNN) which is preliminarily trained to, both or simultaneously: differentiate the first anatomical structure from the second anatomical structure, and convert a real x-ray image into at least one digitally reconstructed radiograph (DRR).

Abstract: A body lift (10) has a wheeled frame (12) and drive motor (42, 44) for moving the frame (12) on its wheels (48, 54). A vertical support (14) extends upward from a base (32) of the wheeled frame (12). Arm and leg support pairs (56, 58 and 78, 80) are movably mounted for translation along the vertical support (14). An elevation motor (28) is connected to lead screw (16) to move the arm and leg support pairs (56, 58 and 78, 80) along the vertical support (14). The leg supports (78, 80) of the leg support pair are laterally pivotable toward and away from each other. A torsion spring (102) is connected to urge the leg supports (78, 80) to a normally outwardly pivoted position. The arm supports (56, 58) of the arm support pair are coupled to pivot the leg supports (78, 80) inward laterally in response to weight applied by a user to the arm supports (56, 58).