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Automatic identification of functional kinematic bone features from MRT segmentation for gait analysis
Author(s) -
Tang Z.,
Pauli J.
Publication year - 2009
Publication title -
materialwissenschaft und werkstofftechnik
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.285
H-Index - 38
eISSN - 1521-4052
pISSN - 0933-5137
DOI - 10.1002/mawe.200900502
Subject(s) - thresholding , segmentation , computer vision , artificial intelligence , femur , vrml , computer science , gait , kinematics , gait analysis , image processing , image segmentation , virtual reality , image (mathematics) , medicine , physics , classical mechanics , surgery , physiology
We present a method for the segmentation of human leg bones and extraction of functional parameters of the femur using MRT images. The novelty consists in the use of dynamic models which will be adapted to the images of individual patients both globally to a whole leg bone and locally to individual parts of a bone. Thresholding and region growing procedures are applied for pre‐processing the images. For some parts of bones, for example the femur ball, we use a three dimensional VRML‐based (Virtual Reality Modelling Language) femur model as a reference in order to make the segmentation method more robust. Based on the segmentation and the 3D VRML model, we can extract functional (biomechanical) femur parameters which are needed for gait analysis.