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Statistical shape models of cuboid, navicular and talus bones

Overview of attention for article published in Journal of Foot and Ankle Research, January 2017
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Title
Statistical shape models of cuboid, navicular and talus bones
Published in
Journal of Foot and Ankle Research, January 2017
DOI 10.1186/s13047-016-0178-x
Pubmed ID
Authors

Aleksandra U. Melinska, Patryk Romaszkiewicz, Justyna Wagel, Bartlomiej Antosik, Marek Sasiadek, D. Robert Iskander

Abstract

The aim was to develop statistical shape models of the main human tarsal bones that would result in novel representations of cuboid, navicular and talus. Fifteen right and 15 left retrospectively collected computed tomography data sets from male individuals, aged from 17 to 63 years, with no known foot pathology were collected. Data were gathered from 30 different subjects. A process of model building includes image segmentation, unifying feature position, mathematical shape description and obtaining statistical shape geometry. Orthogonal decomposition of bone shapes utilising spherical harmonics was employed providing means for unique parametric representation of each bone. Cross-validated classification results based on parametric spherical harmonics representation showed high sensitivity and high specificity greater than 0.98 for all considered bones. The statistical shape models of cuboid, navicular and talus created in this work correspond to anatomically accurate atlases that have not been previously considered. The study indicates high clinical potential of statistical shape modelling in the characterisation of tarsal bones. Those novel models can be applied in medical image analysis, orthopaedics and biomechanics in order to provide support for preoperative planning, better diagnosis or implant design.

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Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 2%
Unknown 51 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 23%
Researcher 8 15%
Student > Bachelor 6 12%
Student > Master 4 8%
Student > Doctoral Student 3 6%
Other 7 13%
Unknown 12 23%
Readers by discipline Count As %
Medicine and Dentistry 14 27%
Engineering 10 19%
Nursing and Health Professions 2 4%
Agricultural and Biological Sciences 2 4%
Social Sciences 2 4%
Other 6 12%
Unknown 16 31%