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![Page 1: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/1.jpg)
Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations
D. Vandermeulen, P. Claes, D. Loeckx, P. SuetensMedical Image Computing (ESAT-Radiology)
S. De Greef, G. WillemsCentre of Forensic Odontology
K.U.Leuven, Faculties of Medicine and Engineering
“Louvre” Seminar March 29 2006
![Page 2: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/2.jpg)
Cranio-facial reconstruction: What?
![Page 3: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/3.jpg)
Manual Craniofacial Reconstruction
• subjective/ artistic talentLots of expertise, both explicit
(documented) and implicit
• Errors by inconsistencies in application
Misalignment of LM on the skull
• time consuming• Only few reconstructions
possible
TAYLOR, K. T. 2001. Forensic Art and Illustration. CRC Press LLC.
Introduction
•Manual
•Computer
•Bias
•Dense LM
Data
Method
Results
Discussion
Conclusion
![Page 4: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/4.jpg)
Computer-based reconstructions
• Small number of tissue thickness measurement landmarks (LMs)
• Independent soft tissue thickness and facial surfaces
• Template-bias: face interpolation with a single facial template (either generic or gender/ancestry/age matched)
http://www.cs.ubc.ca/nest/imager/contributions/katrinaa/recon.html
Introduction
•Manual
•Computer
•Bias
•Dense LM
Data
Method
Results
Discussion
Conclusion
![Page 5: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/5.jpg)
Removing template bias
• Using statistical facial templates to remove bias (Claes et al.)
• Using combined statistical model of facial template and soft tissue thicknesses (Claes et al.)
Fitting Algorithm
. . .
Database
Introduction
•Manual
•Computer
•Bias
•Dense LM
Data
Method
Results
Discussion
Conclusion
![Page 6: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/6.jpg)
Surface and sparse Landmark-based Craniofacial Reconstruction
![Page 7: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/7.jpg)
Dense Landmark model
Warp W
Warp W
target
Reference skull
Reference skin Warped skin
Warped skull
Introduction
•Manual
•Computer
•Bias
•Dense LM
Data
Method
Results
Discussion
Conclusion
![Page 8: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/8.jpg)
Statistical dense LM model
…..
…..
Template database
target
Introduction
•Manual
•Computer
•Bias
•Dense LM
Data
Method
Results
Discussion
Conclusion
![Page 9: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/9.jpg)
CT scan+ Simultaneous visualisation hard & soft tissues- Using ionising radiation
• PM-CT can be used as golden standard?dehydration!
• in-vivo CT on control population? only by lowering radiation dose!
Volumetric Template Data : CTIntroduction
Data
•MR
•CT
•LD-CT
Method
Results
Discussion
Conclusion
![Page 10: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/10.jpg)
Volumetric Template Data : MRI
MRI scan+ Excellent visualisation of soft tissues
- Bone details lost
Introduction
Data
•MR
•CT
•LD-CT
Method
Results
Discussion
Conclusion
![Page 11: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/11.jpg)
Low-Dose CT
• Decrease radiation dose to acceptable (?) level while retaining sufficient quality for diagnosis, therapy or image-based measurements
• Starting from clinical multi-slice spiral CT protocol (Siemens Sensation 16 (Erlangen, Germany)) by lowering the X-ray source current and voltage and increasing the pitch.
• Measured effective radiation dose: 0.18 mSv i.o. 1.5 mSv
• Measuring image quality: thickness differences smaller than a voxel (<0.5 mm).
Introduction
Data
•MR
•CT
•LD-CT
Method
Results
Discussion
Conclusion
![Page 12: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/12.jpg)
CT image preprocessing
• Acquisition and conversion from DICOM to Analyze
• Noise reduction using edge preserving filtering
• Metal artifact removal
• Segmentation of skin and bone surfaces by (hysteresis) thresholding and mathematical morphology
• Implicit Surface representation by signed Distance Transformation
Introduction
Data
Method
Results
Discussion
Conclusion
![Page 13: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/13.jpg)
Implicit Functions for Object Representations and
Transformations:a tentative tutorial
Dirk Vandermeulen
Medical Image Computing
Seminar January 17, 2003
![Page 14: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/14.jpg)
3-D example
Copyright FarField Technology Ltd.
![Page 15: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/15.jpg)
… Shape Morphing
Alternative: interpolate the smooth implicit functions!Example: f(x) = signed distanceG. Turk and J. F. O’Brien, Shape Transformation using Variational Implicit Functions, Siggraph 99
f1(x)>0 f2(x)>0t.f1(x)+(1-t).f2(x)>0
0t1
Shape Transformation Using Variational Implicit Functions, Greg Turk James F. O’Brien, ACM Siggraph99
![Page 16: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/16.jpg)
Implicit Surface Representation
Signed Distance Transform (sDT)Introduction
Data
Method
•MAR
•sDT
•Warping
•Reconstruction
Results
Discussion
Conclusion
![Page 17: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/17.jpg)
Craniofacial reconstruction: method
Warp W
target
Reference skull Warped skull
Warp W
Reference skin Warped skin
Introduction
Data
Method
•MAR
•sDT
•Warping
•Reconstruction
Results
Discussion
Conclusion
![Page 18: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/18.jpg)
Warping method (D.Loeckx et al.)
• Represent warping by tensor-product B-Spline Free Form Deformation (FFD)Introduction
Data
Method
•MAR
•sDT
•Warping
•Reconstruction
Results
Discussion
Conclusion
![Page 19: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/19.jpg)
Warping method (D.Loeckx et al.)
Regularization of FFD by Volume-preserving penalty
![Page 20: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/20.jpg)
Example: template skull to target skull warping
![Page 21: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/21.jpg)
Example: extrapolation to template skin warping
=?
=?
![Page 22: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/22.jpg)
Example: extrapolation to template skin warping
![Page 23: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/23.jpg)
Skin Surface Reconstruction
• Construct (weighted) average of warped skin sDT’s
Introduction
Data
Method
•MAR
•sDT
•Warping
•Reconstruction
Results
Discussion
Conclusion
![Page 24: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/24.jpg)
Example
![Page 25: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/25.jpg)
Validation
• Given only small-sized database (N=20), how to separate into test and validation subsets?
• N-fold Cross-Validation or Leave-one-out CV:– For i=1:NrSubjects
• Reconstruct Subject i from all other subjects in Database• Compare Result to ground truth of i• Evaluate Error
}0/))(ˆ(|{ˆ N
iH
it NxDxS
![Page 26: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/26.jpg)
Qualitative Validation
• Qualitative: 3D reconstructions vs subset of database (face pool comparisons)
Introduction
Data
Method
Results
Discussion
Conclusion
![Page 27: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/27.jpg)
Face pool comparisons
![Page 28: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/28.jpg)
Quantitative Validation I
• Calculate distances between reconstructed and ground truth surface
Introduction
Data
Method
Results
Discussion
Conclusion
|d| = 1.6 ± 1.2 mm
![Page 29: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/29.jpg)
Quantitative Validation I
• Gather error statistics over all subjects• Define M ( 500) test points on a reference head surface
• Find corresponding points on all surfaces by non-rigid surface-based warping (Claes et al.)
• Evaluate error (distance from reconstructed surface to real surface) at test points: mean, std, etc…
![Page 30: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/30.jpg)
Quantitative Validation I: results
Average (1.9mm) Std (1.7mm)
![Page 31: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/31.jpg)
Quantitative Validation II
• Not reconstruction accuracy but recognition accuracy• Based on similarity measure between surfaces or, in this case,
M reference points pi (same as before) on the surfaces S
• Use coordinate-system free representation (invariant to translation/rotation) of surface SEuclidean Distance Matrix ES: ES (i,j) = ||pi-pj||
![Page 32: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/32.jpg)
Quantitative Validation II
• How to measure similarity between two surfaces S1 and S2?
• Compare ES1 to ES2: e.g. – Sum of Squared Differences:
||ES1-ES2|| = i,j>i ( ES1 (i,j) – ES2 (i,j) )2/L >= 0
– (normalized) Cross-Correlation
• Invariance to scaling/size by normalizing EDM with size factor, e.g. geometric mean
NS (i,j) = ES (i,j) / (ES), with (ES) = (ij ES (i,j) )1/L
![Page 33: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/33.jpg)
Quantitative Validation II• Generate Classification Rank Matrix
1 7 20 11 5 4 16 13 3 12 6 15 19 17 8 9 2 18 14 102 6 15 12 19 16 3 5 17 7 11 4 8 20 1 13 18 10 14 93 5 4 16 11 12 7 6 13 15 17 19 2 20 8 1 14 9 10 1813 4 3 14 9 8 16 12 17 5 10 1 11 7 2 15 6 20 19 187 3 11 5 20 1 16 4 6 19 2 12 15 13 17 18 8 9 14 106 15 19 11 2 7 16 12 3 20 5 1 17 13 4 18 8 14 10 95 1 13 6 9 3 14 7 4 16 2 8 11 17 12 20 10 15 19 188 10 14 4 13 17 12 3 9 7 16 15 6 2 1 5 11 20 19 189 7 4 14 8 13 10 3 1 17 5 12 6 16 11 20 15 2 19 1810 8 14 4 13 17 12 7 9 3 16 15 6 1 2 11 5 20 19 1811 5 6 3 20 1 16 19 12 4 15 13 2 7 17 18 8 14 10 912 15 3 16 19 6 2 17 4 20 11 8 5 13 1 7 10 18 14 94 13 14 7 17 8 3 16 10 1 11 15 12 6 9 5 20 2 19 1814 13 8 4 10 9 7 17 3 16 12 1 6 15 11 5 2 20 19 186 12 2 3 15 20 11 16 13 5 17 4 1 8 19 7 10 18 14 916 3 19 12 6 11 4 5 13 17 2 1 15 7 20 8 10 14 18 917 13 12 3 8 4 16 10 2 14 15 6 19 7 11 5 1 20 9 1818 6 19 5 12 11 16 1 2 20 15 3 17 4 13 7 8 10 14 96 16 12 2 19 3 5 11 17 1 15 20 18 4 13 7 8 10 14 920 1 11 5 6 12 3 15 16 7 17 4 19 13 2 18 8 14 10 9
• Correct Rank 1 Classification: 14/20 (13/20)• Correct Rank <= 2 Classification: 16/20 (14/20)
![Page 34: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/34.jpg)
Algorithmic improvements
• Metal Artifact Reduction: using morphology (opening) only in slices ~ artifacts
• Non-rigid registration– fine tuning of regularization parameters to improve skull-
skull matching and extrapolation quality– Alternative deformation models
• Statistical Deformation Models (based on sDT or original CT of database)
– Combination with local models (e.g. nose (De Greef))– Combination with point/surface model (Claes)
• Weighted averaging of sDT– Weights ~ skull overlap– Weights ~ class similarity (gender, age, BMI)– Spatially varying weights
• Statistical Modes of Variation
Introduction
Data
Method
Results
Discussion
Conclusion
![Page 35: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/35.jpg)
Metal ArtifactsIntroduction
Data
Method
Results
Discussion
Conclusion
![Page 36: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/36.jpg)
Metal Artifact RemovalIntroduction
Data
Method
•MAR
•sDT
•Warping
•Reconstruction
Results
Discussion
Conclusion
![Page 37: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/37.jpg)
Algorithmic improvements
• Metal Artifact Reduction: using morphology (opening) only in slices ~ artifacts
• Non-rigid registration– fine tuning of regularization parameters to improve skull-skull
matching and extrapolation quality, again using leave-one-out cross-validation
– Alternative deformation models• Statistical Deformation Models (based on sDT or original CT of
database)
– Combination with local models (e.g. nose (De Greef))– Combination with point/surface model (Claes)
• Weighted averaging of sDT– Weights ~ skull overlap– Weights ~ class similarity (gender, age, BMI)– Spatially varying weights
• Statistical Modes of Variation
Introduction
Data
Method
Results
Discussion
Conclusion
![Page 38: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/38.jpg)
Algorithmic improvements
• Metal Artifact Reduction: using morphology (opening) only in slices ~ artifacts
• Non-rigid registration– fine tuning of regularization parameters to improve skull-
skull matching and extrapolation quality– Alternative deformation models
• Statistical Deformation Models (based on sDT or original CT of database)
– Combination with local models (e.g. nose (De Greef))– Combination with point/surface model (Claes)
• Weighted averaging of sDT– Weights ~ skull overlap– Weights ~ class similarity (gender, age, BMI)– Spatially varying weights
• Statistical Modes of Variation
Introduction
Data
Method
Results
Discussion
Conclusion
![Page 39: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/39.jpg)
Attribute-modulated reconstruction
• All reconstructions so far made with all data in the database, irrespective of gender, age and BMI!
sDT = i wi sDTi , wi = 1/N
![Page 40: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/40.jpg)
Attribute-weighted interpolation• How to bias reconstruction to specific attribute values? (k-)Nearest Neighbour?• Problem: small database, hence weak statistical model (PCA, PLS, …)• Solution(?): “Shape by Example”
– Given attribute values (gender, age, BMI) pi and q of template subjects i and target subject, resp.– Find weight wi(q) to apply to sDTi in weighted average
sDT = I wi(q) sDTi , wi(pj) ij
– Determined using RBF smoothest approximation
![Page 41: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/41.jpg)
Example
![Page 42: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/42.jpg)
Example
All Females only Males only
AWI Females+BMI Ground truth
![Page 43: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/43.jpg)
Algorithmic improvements
• Metal Artifact Reduction: using morphology (opening) only in slices ~ artifacts
• Non-rigid registration– fine tuning of regularization parameters to improve skull-
skull matching and extrapolation quality– Alternative deformation models
• Statistical Deformation Models (based on sDT or original CT of database)
• Weighted averaging of sDT– Weights ~ skull overlap– Weights ~ class similarity (gender, age, BMI)– Spatially varying weights
• Statistical Modes of Variation
Introduction
Data
Method
Results
Discussion
Conclusion
![Page 44: Computerized Craniofacial Reconstruction using CT-derived Implicit Surface Representations D. Vandermeulen, P. Claes, D. Loeckx, P. Suetens Medical Image.](https://reader036.fdocuments.us/reader036/viewer/2022081602/5518a3b7550346881f8b49b0/html5/thumbnails/44.jpg)
Conclusion
• “Proof of concept” of volumetric cranio-facial reconstruction
• Validation procedure required on a representative database
• Metal Artifact Reduction is required • Missing Data problem using deformation model• Comments?
Introduction
Data
Method
Results
Discussion
Conclusion