Foot Abnormality Mapping using Statistical Shape Modelling - 16.070

K. Stankovic et al., "Foot Abnormality Mapping using Statistical Shape Modelling", in Proc. of 7th Int. Conf. on 3D Body Scanning Technologies, Lugano, Switzerland, 2016, pp. 70-79, https://doi.org/10.15221/16.070.

Title:

Foot Abnormality Mapping using Statistical Shape Modelling

Authors:

Kristina STANKOVIC 1, Femke DANCKAERS 1, Brian G. BOOTH 1,
Fien BURG 2, Saartje DUERINCK 2, Jan SIJBERS 1, Toon HUYSMANS 1

1 iMinds - Vision Lab, Dept. of Physics, University of Antwerp, Belgium;
2 RSscan International NV, Paal, Belgium

Abstract:

About 20% of the population suffer from disabling foot or ankle pain that require the use of foot orthotics. Traditionally, those foot orthotics are designed manually, but digital procedures are desired to provide a faster, more objective, and more reliable workflow. In this study, we introduce a method for detecting shape abnormalities in feet for the purposes of pathology diagnosis and orthotic design. The proposed method consists of two phases. In the training phase, a statistical 3D foot model (based on 42 healthy subjects) is built. In the test phase, the landmarks of a new 3D foot scan are compared to the trained model. A landmark is detected as an outlier if it is in the extreme ranges. This testing process is repeated at all landmarks to identify all abnormal foot regions. Preliminary results show that, when testing a foot of a known pathology (hallux valgus, heel spur, foot pronation), we are able to detect abnormal regions accurately. We also examined the effect of using rigid or similarity-based alignment during 3D model building and abnormality detection. We show that our proposed method is a faster and a more objective approach than traditional approaches for abnormality detection of the foot. As such, this method may prove useful in the medical diagnosis of foot pathologies and in automated orthotic design.

Details:

Full paper: 16.070.pdf
Proceedings: 3DBST 2016, 30 Nov.-1 Dec. 2016, Lugano, Switzerland
Pages: 70-79
DOI: 10.15221/16.070

License/Copyright notice:

Proceedings: © Hometrica Consulting - Dr. Nicola D'Apuzzo, Switzerland, hometrica.ch.
Authors retain all rights to individual papers, which are licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The papers appearing in the proceedings reflect the author's opinions. Their inclusion in the proceedings does not necessary constitute endorsement by the editor or by the publisher.

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