
Template‐based landmark and region mapping of bone
Author(s) -
Kim Jaeil,
Seo Sang Gyo,
Lee Dong Yeon,
Park Jinah
Publication year - 2014
Publication title -
journal of foot and ankle research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.763
H-Index - 39
ISSN - 1757-1146
DOI - 10.1186/1757-1146-7-s1-a42
Subject(s) - landmark , point distribution model , artificial intelligence , computer vision , curvature , orientation (vector space) , computer science , deformation (meteorology) , geometry , pattern recognition (psychology) , anatomy , mathematics , medicine , geology , oceanography
Background The shape morphology using 3D surface models has been recently emerged for biomechanics research, such as the quantitative assessment of bone deformity with clinical factors [1] and the correlation analysis between bone shape and joint motion [2]. In the bone shape morphology, the morphological difference of the bones across subjects is quantified by the geometric measures, such as the curvature of the articular surface and the relative bone orientation in joints, defined with the anatomical landmarks and regions on the bone surface. However, the landmark and region determination on individual cases is a difficult and time-consuming task, because of the various size and shape of the bones and operator’s errors. In this paper, we propose an automated landmark and region mapping method based on a non-rigid template-toimage registration. The template model is a triangular mesh including the generic shape of the target. It also encodes the landmarks and regions as a subset of the points in the triangular mesh. For the landmark and region mapping to individual bones, the template model is nonrigidly deformed by a Laplacian deformation framework [3]. This framework derives the point transformation into the image boundary while minimizing the distortion of the point distribution in the template model. This behavior of the deformation framework helps to trace the positions of the anatomical landmarks and regions across subjects.