DEIT-Based Bone Position and Orientation Estimation for Robotic Support in Total Knee Arthroplasty—A Computational Feasibility Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Forward Simulation and Inverse Estimation of Conductivity
2.2. Segmentation of Bone Structures
- Remove any values of elements close to electrodes;
- Sort remaining in ascending order and label sorted ;
- Compute slope for all N sorted samples;
- Pick all including any in between first and last ;
- Fit line to with ;
- Compute
- Split the half-open interval into bins;
- Split the half-open interval into bins.
- Set the highest considered bin ;
- Select the first tetrahedral element
- If all are either assigned or discarded, stop;
- If , discard and continue from step 3 with ;
- If has been assigned to a cluster K, continue from step 3 with
- Create new cluster ;
- Assign to new cluster
- Collect all tetrahedral elements adjacent to the four faces of
- Discard any for which holds;
- Skip any already assigned to a cluster K;
- Push remaining to work queue for further processing;
- If is empty, store cluster and continue from step 3 with ;
- Pop first from and continue from step 7 with .
2.3. Bone Position and Axial Orientation
3. Results
4. Discussion
5. Conclusions and Outlook
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
TKA | Total knee arthroplasty |
CT | Computed X-ray tomography |
EIT | Electrical Impedance Tomography |
AEIT | Absolute Electrical Impedance Tomography |
DEIT | Differential Electrical Impedance Tomography |
TDEIT | Time-Differential Electrical Impedance Tomography |
FEM | Finite Element Model |
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Tissue | Skin | Fat | Muscle | Bone | Marrow |
---|---|---|---|---|---|
Conductivity | 0.065 | 0.03 | 0.37 | 0.02 | 0.002 |
Electrodes | Number | 16 |
Type | Ag/AgCl | |
Diameter | 7 mm | |
Stimulation | Pattern | opposite electrodes |
Current | 10 mA | |
Regularization | 0.00007 |
Tissue Configuration | ||||||||
---|---|---|---|---|---|---|---|---|
Model | Muscle | Skin | Fat | Initial | Optimal | Initial | Optimal | |
Subcut. | Inter | |||||||
Cylinder | X | – | – | – | 1.4 | 1.1 | 0.72 | 1.14 |
X | X | X | – | 2.8 | 1.3 | 0.86 | 0.20 | |
Realistic | X | – | – | – | 7.9 | 8.0 | 5.42 | 2.90 |
X | X | X | – | 24.8 | 21.0 | 1.76 | 0.56 | |
X | X | X | X | 14.0 | 14.4 | 3.39 | 2.63 | |
mean | – | – | – | – | 10.2 | 9.2 | 2.43 | 1.49 |
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Schrott, J.; Affortunati, S.; Stadler, C.; Hintermüller, C. DEIT-Based Bone Position and Orientation Estimation for Robotic Support in Total Knee Arthroplasty—A Computational Feasibility Study. Sensors 2024, 24, 5269. https://doi.org/10.3390/s24165269
Schrott J, Affortunati S, Stadler C, Hintermüller C. DEIT-Based Bone Position and Orientation Estimation for Robotic Support in Total Knee Arthroplasty—A Computational Feasibility Study. Sensors. 2024; 24(16):5269. https://doi.org/10.3390/s24165269
Chicago/Turabian StyleSchrott, Jakob, Sabrina Affortunati, Christian Stadler, and Christoph Hintermüller. 2024. "DEIT-Based Bone Position and Orientation Estimation for Robotic Support in Total Knee Arthroplasty—A Computational Feasibility Study" Sensors 24, no. 16: 5269. https://doi.org/10.3390/s24165269