Automated geometric features evaluation method for normal foot skeleton model

  • Authors:
  • Bartosz Borucki;Krzysztof NowińSki;Michał Chlebiej;Andrzej Rutkowski;Paweł Adamczyk;Jacek Laskowski

  • Affiliations:
  • Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw, Żwirki i Wigury 93, 02-089 Warsaw, Poland;Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw, Żwirki i Wigury 93, 02-089 Warsaw, Poland;Faculty of Mathematics and Computer Science, N. Copernicus University, Chopina 12/18, 87-100 Toruń, Poland;Faculty of Mathematics and Computer Science, N. Copernicus University, Chopina 12/18, 87-100 Toruń, Poland;Carolina Medical Center, Pory 78, 02-757 Warsaw, Poland;Carolina Medical Center, Pory 78, 02-757 Warsaw, Poland

  • Venue:
  • Annales UMCS, Informatica
  • Year:
  • 2011

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Abstract

"Normal foot model" is a geometric model of a healthy human foot. As the comparison of the processed feet requires a reference ideal healthy foot parameterization it was necessary to create such a model by defining skeleton geometric features and generating the feature set on a dataset population. Manual positioning of such number of landmarks is both a complex and time consuming task for a skilled radiologist, not to mention the total cost of such a procedure. Thus it was recommended to formulate an automated computer algorithm to perform this procedure with accuracy at a comparable level as the manual process. The following paper describes our approach based on automatic landmark positioning in a volumetric foot dataset. The proposed automated procedure is based on four main steps: manual landmark positioning on a reference dataset, registration of the reference dataset with the examined study, transformation of landmark positions from the reference dataset space into the examined dataset space, and calculation of the geometric features on the basis of landmarks positions. The results of our algorithm are presented and discussed in the context of pros and cons of the automated method itself as well as in the context of the generated normal foot model.