Human contour segmentation algorithm for radiotherapy-assisted positioning

In this paper, a body contour segmentation algorithm for assisting radiotherapy patient posing is investigated. The image data of radiotherapy patients with body parts are captured using an RGB-D camera, and the U²-Net network model is improved to segment the body contour of radiotherapy patients wearing thermoplastic membranes and fixed stents by adding CBAM and CA attention mechanisms. The body contours acquired in the CT simulation localization room are displayed in the computer equipment in the radiotherapy room, thus helping the radiotherapist to restore the real-time posture of the patient in the radiotherapy room approximately to the same position in the CT localization room. The results show that the evaluation indexes of this segmentation algorithm can reach 98.7% for PA, 95.8% for IOU, and 0.969 for DSC, which can achieve a better segmentation effect, and the extracted patient contour is more accurate, smooth, and less noisy. Therefore, the algorithm can help radiotherapists to accomplish the task of assisted posing.