Evidence map›Paper›PMID 27038965›Full record

ArticleInternational journal of computer assisted radiology and surgery2016

Fully automatic reconstruction of personalized 3D volumes of the proximal femur from 2D X-ray images.

Weimin Yu, Chengwen Chu, Moritz Tannast, Guoyan Zheng

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Article in International journal of computer assisted radiology and surgery, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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8citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
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  4. [Rapid femur modeling method based on statistical shape model].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2022
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Weimin YuInstitute for Surgical Technology and Biomechanics, University of Bern, Stauffacherstr. 78, Bern, 3014, Switzerland.
Chengwen ChuInstitute for Surgical Technology and Biomechanics, University of Bern, Stauffacherstr. 78, Bern, 3014, Switzerland.
Moritz TannastDepartment of Orthopaedic Surgery, Inselspital, University of Bern, Bern, Switzerland.
Guoyan ZhengInstitute for Surgical Technology and Biomechanics, University of Bern, Stauffacherstr. 78, Bern, 3014, Switzerland. guoyan.zheng@ieee.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAccurate preoperative planning is crucial for the outcome of total hip arthroplasty. Recently, 2D pelvic X-ray radiographs have been replaced by 3D CT. However, CT suffers from relatively high radiation dosage and cost. An alternative is to reconstruct a 3D patient-specific volume data from 2D X-ray images.

methodsIn this paper, based on a fully automatic image segmentation algorithm, we propose a new control point-based 2D-3D registration approach for a deformable registration of a 3D volumetric template to a limited number of 2D calibrated X-ray images and show its application to personalized reconstruction of 3D volumes of the proximal femur. The 2D-3D registration is done with a hierarchical two-stage strategy: the scaled-rigid 2D-3D registration stage followed by a regularized deformable B-spline 2D-3D registration stage. In both stages, a set of control points with uniform spacing are placed over the domain of the 3D volumetric template first. The registration is then driven by computing updated positions of these control points with intensity-based 2D-2D image registrations of the input X-ray images with the associated digitally reconstructed radiographs, which allows computing the associated registration transformation at each stage.

resultsEvaluated on datasets of 44 patients, our method achieved an overall surface reconstruction accuracy of [Formula: see text] and an average Dice coefficient of [Formula: see text]. We further investigated the cortical bone region reconstruction accuracy, which is important for planning cementless total hip arthroplasty. An average cortical bone region Dice coefficient of [Formula: see text] and an inner cortical bone surface reconstruction accuracy of [Formula: see text] were found.

conclusionsIn summary, we developed a new approach for reconstruction of 3D personalized volumes of the proximal femur from 2D X-ray images. Comprehensive experiments demonstrated the efficacy of the present approach.

Indexed as

AlgorithmsCalibrationFemurHumansImaging, Three-DimensionalTomography, X-Ray Computed2D–3DB-splineDeformable registrationRandom forest regressionReconstructionSegmentation

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.