Adriaan Lambrechts
Roel Wirix-Speetjens
Frederik Maes3,4
Sabine Van Huffel
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- 1Materialise NV, Leuven, Belgium
- 2Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium
- 3Department of Electrical Engineering (ESAT), Processing Speech and Images (PSI), KU Leuven, Leuven, Belgium
- 4Medical Imaging Research Center, UZ Leuven, Leuven, Belgium
A Corrigendum on
Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty
by Lambrechts, A., Wirix-Speetjens, R., Maes, F. and Van Huffel, S. (2022). Frontiers in Robotics and AI. 9:840282. doi: 10.3389/frobt.2022.840282
In the original article, the “Statistical shape model-based prediction of tibiofemoral cartilage” was not cited. The citation has now been inserted in the section Materials and Methods, “Data Preprocessing,” Paragraph 5 and should read:
“The DOFs in the MPPs were also used as features because they provide a baseline on which the model needs to learn the necessary changes. The final set of features is shape coefficients obtained after fitting a statistical shape model (SSM) to the bones. An SSM describes the distribution of anatomical variation in a population of geometrical shapes (Cootes et al., 1995). The SSM describes a new bone as the average bone shape from the population together with a linear combination of the shape variation modes. The SSM was created based on a dataset of 524 3D models of femur and tibia (Van Dijck et al., 2018). The first fifteen shape coefficients of both femur and tibia, explaining most of the shape variation, are included as features.”
An Acknowledgements section was also not included in the published article. A corrected statement appears below.
“The authors gratefully acknowledge Christophe Van Dijck for the construction of the knee statistical shape models.”
The authors apologize for these errors and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
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Reference
Keywords: total knee arthroplasty, patient-specific, preoperative planning, machine learning, orthopedic surgery, artificial intelligence
Citation: Lambrechts A, Wirix-Speetjens R, Maes F and Van Huffel S (2022) Corrigendum: Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty. Front. Robot. AI 9:899349. doi: 10.3389/frobt.2022.899349
Received: 18 March 2022; Accepted: 06 April 2022;
Published: 28 April 2022.
Edited and reviewed by:
Daniele Cafolla, Mediterranean Neurological Institute Neuromed (IRCCS), ItalyCopyright © 2022 Lambrechts, Wirix-Speetjens, Maes and Van Huffel. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Adriaan Lambrechts, YWRyaWFhbi5sYW1icmVjaHRzQGhvdG1haWwuY29t