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Computational and Mathematical Methods in Medicine
Volume 2017 (2017), Article ID 2938504, 13 pages
https://doi.org/10.1155/2017/2938504
Research Article

Assessment of Iterative Closest Point Registration Accuracy for Different Phantom Surfaces Captured by an Optical 3D Sensor in Radiotherapy

1Institute for Information Technology and Communication Engineering, Otto-von-Guericke University Magdeburg, Universitätsplatz 2, 39016 Magdeburg, Germany
2Clinic for Radiotherapy, Otto-von-Guericke University Magdeburg, Leipziger Straße 44, 39120 Magdeburg, Germany

Correspondence should be addressed to Gerald Krell; ed.ugvo@llerk

Received 4 July 2016; Revised 30 September 2016; Accepted 25 October 2016; Published 9 January 2017

Academic Editor: Ayman El-Baz

Copyright © 2017 Gerald Krell et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Gerald Krell, Nazila Saeid Nezhad, Mathias Walke, Ayoub Al-Hamadi, and Günther Gademann, “Assessment of Iterative Closest Point Registration Accuracy for Different Phantom Surfaces Captured by an Optical 3D Sensor in Radiotherapy,” Computational and Mathematical Methods in Medicine, vol. 2017, Article ID 2938504, 13 pages, 2017. doi:10.1155/2017/2938504