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Technical Brief

Shape Analysis of the Femoral Head: A Comparative Study Between Spherical, (Super)Ellipsoidal, and (Super)Ovoidal Shapes

[+] Author and Article Information
Daniel Simões Lopes

Visualization and Intelligent Multimodal Interfaces Group,
INESC ID Lisboa,
Rua Alves Redol, 9,
Lisbon 1000-029, Portugal
e-mail: daniel.lopes@inesc-id.pt

Richard R. Neptune

Mem. ASME
Department of Mechanical Engineering,
The University of Texas at Austin,
Austin, TX 78712
e-mail: rneptune@mail.utexas.edu

Artur A. Gonçalves

Instituto Superior Técnico,
Universidade de Lisboa,
Avenida Rovisco Pais 1,
Lisbon 1049-001, Portugal
e-mail: artur.goncalves@tecnico.ulisboa.pt

Jorge A. Ambrósio

Instituto Superior Técnico,
Universidade de Lisboa,
Avenida Rovisco Pais 1,
Lisbon 1049-001, Portugal
e-mail: jorge@dem.ist.utl.pt

Miguel T. Silva

Instituto Superior Técnico,
Universidade de Lisboa,
Avenida Rovisco Pais 1,
Lisbon 1049-001, Portugal
e-mail: MiguelSilva@ist.utl.pt

1Corresponding author.

Manuscript received April 10, 2015; final manuscript received September 13, 2015; published online October 1, 2015. Assoc. Editor: Tammy L. Haut Donahue.

J Biomech Eng 137(11), 114504 (Oct 01, 2015) (8 pages) Paper No: BIO-15-1160; doi: 10.1115/1.4031650 History: Received April 10, 2015; Revised September 13, 2015

In this work, MacConaill's classification that the articular surface of the femoral head is better represented by ovoidal shapes rather than purely spherical shapes is computationally tested. To test MacConaill's classification, a surface fitting framework was developed to fit spheres, ellipsoids, superellipsoids, ovoids, and superovoids to computed tomography (CT) data of the femoral proximal epiphysis. The framework includes several image processing and computational geometry techniques, such as active contour segmentation and mesh smoothing, where implicit surface fitting is performed with genetic algorithms. By comparing the surface fitting error statistics, the results indicate that (super)ovoids fit femoral articular surfaces better than spherical or (super)ellipsoidal shapes.

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Figures

Grahic Jump Location
Fig. 1

Unit-sized superellipsoids and superovoids for varying exponent values

Grahic Jump Location
Fig. 2

Computational framework for information extraction and geometric modeling of spheroidal articular surfaces. An implicit shape model is fitted to medical image data, thus providing quantitative information regarding global geometric characteristics. File formats and software tools are shown. The software versions used are itk-snap 2.2.0, paraview 3.10.1, blender 2.43, and matlab® R2009b.

Grahic Jump Location
Fig. 3

Three-dimensional views of the optimally fitted surfaces of a femoral head illustrating that the geometric primitives fit the data in a global fashion. Data points are represented based on the minimal signed Euclidean distances (in millimeter) calculated between each point and the idealized geometric primitive.

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