Neural network-based visual body weight estimation for drug dosage finding

Christian Pfitzner; Stefan May; Andreas Nüchter

doi:10.1117/12.2216042

21 March 2016 Neural network-based visual body weight estimation for drug dosage finding

Christian Pfitzner, Stefan May, Andreas Nüchter

Proceedings Volume 9784, Medical Imaging 2016: Image Processing; 97841Z (2016) https://doi.org/10.1117/12.2216042
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Body weight adapted drug dosages are important for emergency treatments: Inaccuracies in body weight estimation may lead to inaccurate drug dosing. This paper describes an improved approach to estimating the body weight of emergency patients in a trauma room, based on images from an RGB-D and a thermal camera. The improvements are specific to several aspects: Fusion of RGB-D and thermal camera eases filtering and segmentation of the patient's body from the background. Robustness and accuracy is gained by an artificial neural network, which considers geometric features from the sensors as input, e.g. the patient's volume, and shape parameters. Preliminary experiments with 69 patients show an accuracy close to 90 percent, with less than 10 percent relative error and the results are compared with the physician's estimate, the patient's statement and an established anthropometric method.

Citation Download Citation

Christian Pfitzner, Stefan May, and Andreas Nüchter "Neural network-based visual body weight estimation for drug dosage finding", Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 97841Z (21 March 2016); https://doi.org/10.1117/12.2216042

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