Seeing under the cover with a 3D U-Net: point cloud-based weight estimation of covered patients.
Journal:
International journal of computer assisted radiology and surgery
Published Date:
Aug 21, 2021
Abstract
PURPOSE: Body weight is a crucial parameter for patient-specific treatments, particularly in the context of proper drug dosage. Contactless weight estimation from visual sensor data constitutes a promising approach to overcome challenges arising in emergency situations. Machine learning-based methods have recently been shown to perform accurate weight estimation from point cloud data. The proposed methods, however, are designed for controlled conditions in terms of visibility and position of the patient, which limits their practical applicability. In this work, we aim to decouple accurate weight estimation from such specific conditions by predicting the weight of covered patients from voxelized point cloud data.