Automated geometric features evaluation method for normal foot skeleton model

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. *

Body Metabolism and Exercise

“…In contrast, the VisNow software used in the present study is suitable for the analysis of both MRI and CT images and it enables the manual inclusion of the fourth ventricle and cerebral aqueduct into the volume of intracranial CSF ventricular systems, which provides more dependable results. The reliability of the VisNow software in clinical diagnostics has been confirmed in other recent studies (Kapiński et al 2013;Borucki et al 2011Borucki et al , 2012.…”