Anatomical landmark and region mapping
based on a template surface deformation
for foot bone morphology
Jaeil Kim1, Sang Gyo Seo2, Dong Yeon Lee2, Jinah Park1
1 Department of Computer Science, KAIST, South Korea
2 Orthopedic Surgery, Seoul National University Hospital, South Korea
< Anatomical landmark and region mapping
based on a template surface deformation
for foot bone morphology >
< Jaeil Kim >
My disclosure is in the
Final AOFAS Mobile App.
I have no potential conflicts with
this presentation.
Introduction
• Anatomical point and region landmarks provide a basis to
quantify the morphological changes of bones and the joint
orientation/motion based on anatomical knowledge [1-2]
• However, determining the
landmarks on the bone
surfaces is a difficult and
time-consuming task, due
to the large variations of
size and shape, and the lack
of the salient features of the
landmarks
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How to define the sub-regions of bone surfaces consistently?
[ Volume Rendering (left) and bone surface meshes (right) ]
AOFAS 2014 Annual Meeting
Contributions
• We propose a template-based landmark mapping method for the
consistent and automated landmark assignment on individuals’ bone
surfaces.
• Template model in our approach
– Encoding the generic shape features of the structure as a surface mesh
– Including the anatomical landmarks as subsets of the points of the surface
mesh
• Proposed template-based landmark mapping
– Building a pairwise correspondence between the template and the target
volume
– Achieved by a non-rigid surface-to-volume registration technique
– To place the anatomical landmarks and compare them via transitive relation
between subjects 8/13/2014 4 AOFAS 2014 Annual Meeting
Outline
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Segmentation
1. Template Model
with Landmarks
1.5 (mm) 0.0 Point Displacement
2. Non-rigid Template-to-Volume Registration
with Shape Correspondence
3. Individualized Model
and Landmarks
AOFAS 2014 Annual Meeting
• Template surface model
– Generated from an image atlas of target structures
– Image atlas = mean shape image of the input binary masks
– Marching cubes algorithm + regular surface sampling
• Anatomical region and point landmarks
– Assigned manually onto
the template surface model
– We used a point selection tool
in the Paraview software
(www.paraview.org, version 4.1.0)
– Save the landmarks as subsets
of the point indices of the
template model
Template Construction
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[Template model and region landmark]
Template-to-Volume
Registration • Two steps of template-to-volume registration
– 1st step: a rigid alignment of the template model to target volume using
iterative closest point algorithm
– 2nd step: a non-rigid template deformation to boundaries
• A progressive deformation based on a Laplacian surface representation and a
flexible weighting scheme of rigidity [3]
• Preserving the geometric features (relative area of triangles and local curvature)
as strong as possible during the template surface deformation
• To place the points of the template to anatomically corresponded positions on the
target volume
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[Objective function of the Laplacian surface deformation]
AOFAS 2014 Annual Meeting
Experiments on Human Data
- Calcaneus Study
• Materials
– CT scans of 10 non-diseased subjects
– Modeling the calcaneus using the template model, generated from the mean image of
all binary masks
– Template surface sampling: 1.016~2.392mm (distance between points)
• Landmark assignment to template model
– Anterior, middle and posterior articular surface for the talus
• Experiments
– Evaluation of the template-to-volume registration
• Measuring the shape similarity between the template and the binary masks using volume
overlap and distance metrics (mean and Hausdorff distances)
– Evaluation of the landmark mapping
• Comparing the template-based landmarks with manually assigned landmarks on individuals’
surface models
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Experiments on Human Data
- Calcaneus Study
• Accuracy of the template-to-volume registration
• Comparison of the template-based landmarks with manually
assigned landmarks
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Experiments on Human Data
- Calcaneus Study
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[Maximum distance btw manual and template-based landmarks]
[Minimum distance btw manual and template-based landmarks]
CT Volume Rendering Surface Model Manual Landmark Template-based Landmark
Summary
• Template-based landmark mapping framework
– Using a template-to-volume registration finding the pairwise
correspondence between the template and target volume
– Provide an accurate surface representation and the
individualized positions of the anatomical landmarks
• Future directions
– Statistical analysis of the landmark correspondence across
multiple subjects
– Application to large datasets including subjects with disorders of
foot and ankle
– Correlation analysis between joint motion and shape changes
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References & Acknowledgements
• References
1. Neogi, T., et al.: Magnetic resonance imaging-based three-dimensional bone shape
of the knee predicts onset of knee osteoarthritis: data from the osteoarthritis
initiative. Arthritis Rheum. 2013. 65:2048–2058.
2. Peeters, K., et al.: Alterated talar and navicular bone morphology is associated with
pes planus deformity: A CT-scan study. J Orthop Res. 2012. 31:282–287.
3. Kim, J. ,Park, J.: Organ Shape Modeling Based on the Laplacian Deformation
Framework for Surface-Based Morphometry Studies. J Comp Sci Eng. 2012. 6:219-
226
• Acknowledgements
– This research was supported by Basic Science Research Program through the
National Research Foundation of Korea (NRF) funded by the Ministry of Education,
Science and Technology (No. 2011-0009761)
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