3D Reconstruction of Dental Specimens from 2D Histological Images and muCt-Scans

A. Rahimi, L. Keilig, Gerhard H. Bendels, Reinhard Klein, T. Buzug, I. Abdelgader, M. Abboud und C. Bourauel
In: Computer Methods in Biomechanics and Biomedical Engineering (Aug. 2005), 8:3(167-176)
 

Abstract

Direct comparison of experimental and theoretical results in biomechanical studies requires a careful reconstruction of specimen surfaces to achieve a satisfactory congruence for validation. In this paper a semi-automatic approach is described to reconstruct triangular boundary representations from images originating from, either histological sections or muCT-, CT- or MRI-data, respectively. In a user-guided first step, planar 2D contours were extracted for every material of interest, using image segmentation techniques. In a second step, standard 2D triangulation algorithms were used to derive high quality mesh representations of the underlying surfaces. This was accomplished by converting the 2D meshes into 3D meshes by a novel lifting procedure. The meshes can be imported as is into finite element programme packages such as Marc/Mentat or COSMOS/M. Accuracy and feasibility of the algorithm is demonstrated by reconstructing several specimens as examples and comparing simulated results with available measurements performed on the original objects.

Bibtex

@ARTICLE{rahimi-2005-3d-reconstruction,
    author = {Rahimi, A. and Keilig, L. and Bendels, Gerhard H. and Klein, Reinhard and Buzug, T. and Abdelgader,
              I. and Abboud, M. and Bourauel, C.},
     pages = {167--176},
     title = {3D Reconstruction of Dental Specimens from 2D Histological Images and muCt-Scans},
   journal = {Computer Methods in Biomechanics and Biomedical Engineering},
    volume = {8},
    number = {3},
      year = {2005},
     month = aug,
  abstract = {Direct comparison of experimental and theoretical results in biomechanical studies requires a
              careful reconstruction of specimen surfaces to achieve a satisfactory congruence for validation. In
              this paper a semi-automatic approach is described to reconstruct triangular boundary representations
              from images originating from, either histological sections or muCT-, CT- or MRI-data, respectively.
              In a user-guided first step, planar 2D contours were extracted for every material of interest, using
              image segmentation techniques. In a second step, standard 2D triangulation algorithms were used to
              derive high quality
              mesh representations of the underlying surfaces. This was accomplished by converting the 2D meshes
              into 3D meshes by a novel lifting procedure. The meshes can be imported as is into finite element
              programme packages such as Marc/Mentat or COSMOS/M. Accuracy and feasibility of the algorithm is
              demonstrated by reconstructing several specimens as examples and comparing simulated results with
              available measurements performed on the original objects.}
}