Literature DB >> 21621977

Diagnostic radiograph based 3D bone reconstruction framework: application to the femur.

P Gamage1, S Q Xie, P Delmas, W L Xu.   

Abstract

Three dimensional (3D) visualization of anatomy plays an important role in image guided orthopedic surgery and ultimately motivates minimally invasive procedures. However, direct 3D imaging modalities such as Computed Tomography (CT) are restricted to a minority of complex orthopedic procedures. Thus the diagnostics and planning of many interventions still rely on two dimensional (2D) radiographic images, where the surgeon has to mentally visualize the anatomy of interest. The purpose of this paper is to apply and validate a bi-planar 3D reconstruction methodology driven by prominent bony anatomy edges and contours identified on orthogonal radiographs. The results obtained through the proposed methodology are benchmarked against 3D CT scan data to assess the accuracy of reconstruction. The human femur has been used as the anatomy of interest throughout the paper. The novelty of this methodology is that it not only involves the outer contours of the bony anatomy in the reconstruction but also several key interior edges identifiable on radiographic images. Hence, this framework is not simply limited to long bones, but is generally applicable to a multitude of other bony anatomies as illustrated in the results section.
Copyright © 2010 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21621977     DOI: 10.1016/j.compmedimag.2010.09.008

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  3 in total

1.  Improving Visibility of Stereo-Radiographic Spine Reconstruction with Geometric Inferences.

Authors:  Sampath Kumar; K Prabhakar Nayak; K S Hareesha
Journal:  J Digit Imaging       Date:  2016-04       Impact factor: 4.056

2.  Radiographic reconstruction of lower-extremity bone fragments: a first trial.

Authors:  Steffen Schumann; Richard Bieck; Rainer Bader; Johannes Heverhagen; Lutz-P Nolte; Guoyan Zheng
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-06-16       Impact factor: 2.924

3.  Statistical Analyses of Femur Parameters for Designing Anatomical Plates.

Authors:  Lin Wang; Kunjin He; Zhengming Chen
Journal:  Comput Math Methods Med       Date:  2016-12-01       Impact factor: 2.238

  3 in total

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