Statistical shape model-based reconstruction of a scaled, patient-specific surface model of the pelvis from a single standard AP x-ray radiograph
- PMID: 20443464
- DOI: 10.1118/1.3327453
Statistical shape model-based reconstruction of a scaled, patient-specific surface model of the pelvis from a single standard AP x-ray radiograph
Abstract
Purpose: The aim of this article is to investigate the feasibility of using a statistical shape model (SSM)-based reconstruction technique to derive a scaled, patient-specific surface model of the pelvis from a single standard anteroposterior (AP) x-ray radiograph and the feasibility of estimating the scale of the reconstructed surface model by performing a surface-based 3D/3D matching.
Methods: Data sets of 14 pelvises (one plastic bone, 12 cadavers, and one patient) were used to validate the single-image based reconstruction technique. This reconstruction technique is based on a hybrid 2D/3D deformable registration process combining a landmark-to-ray registration with a SSM-based 2D/3D reconstruction. The landmark-to-ray registration was used to find an initial scale and an initial rigid transformation between the x-ray image and the SSM. The estimated scale and rigid transformation were used to initialize the SSM-based 2D/3D reconstruction. The optimal reconstruction was then achieved in three stages by iteratively matching the projections of the apparent contours extracted from a 3D model derived from the SSM to the image contours extracted from the x-ray radiograph: Iterative affine registration, statistical instantiation, and iterative regularized shape deformation. The image contours are first detected by using a semiautomatic segmentation tool based on the Livewire algorithm and then approximated by a set of sparse dominant points that are adaptively sampled from the detected contours. The unknown scales of the reconstructed models were estimated by performing a surface-based 3D/3D matching between the reconstructed models and the associated ground truth models that were derived from a CT-based reconstruction method. Such a matching also allowed for computing the errors between the reconstructed models and the associated ground truth models.
Results: The technique could reconstruct the surface models of all 14 pelvises directly from the landmark-based initialization. Depending on the surface-based matching techniques, the reconstruction errors were slightly different. When a surface-based iterative affine registration was used, an average reconstruction error of 1.6 mm was observed. This error was increased to 1.9 mm, when a surface-based iterative scaled rigid registration was used.
Conclusions: It is feasible to reconstruct a scaled, patient-specific surface model of the pelvis from single standard AP x-ray radiograph using the present approach. The unknown scale of the reconstructed model can be estimated by performing a surface-based 3D/3D matching.
Similar articles
-
2D/3D reconstruction of the distal femur using statistical shape models addressing personalized surgical instruments in knee arthroplasty: A feasibility analysis.Int J Med Robot. 2017 Dec;13(4). doi: 10.1002/rcs.1823. Epub 2017 Apr 7. Int J Med Robot. 2017. PMID: 28387436
-
3D reconstruction of a patient-specific surface model of the proximal femur from calibrated x-ray radiographs: a validation study.Med Phys. 2009 Apr;36(4):1155-66. doi: 10.1118/1.3089423. Med Phys. 2009. PMID: 19472621
-
A 2D/3D correspondence building method for reconstruction of a patient-specific 3D bone surface model using point distribution models and calibrated X-ray images.Med Image Anal. 2009 Dec;13(6):883-99. doi: 10.1016/j.media.2008.12.003. Epub 2008 Dec 24. Med Image Anal. 2009. PMID: 19162529
-
Review of 2-D/3-D Reconstruction Using Statistical Shape and Intensity Models and X-Ray Image Synthesis: Toward a Unified Framework.IEEE Rev Biomed Eng. 2019;12:269-286. doi: 10.1109/RBME.2018.2876450. Epub 2018 Oct 17. IEEE Rev Biomed Eng. 2019. PMID: 30334808 Review.
-
A Methodological Review of 3D Reconstruction Techniques in Tomographic Imaging.J Med Syst. 2018 Sep 4;42(10):190. doi: 10.1007/s10916-018-1042-2. J Med Syst. 2018. PMID: 30178184 Review.
Cited by
-
Statistical model-based segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs.Int J Comput Assist Radiol Surg. 2014 Mar;9(2):165-76. doi: 10.1007/s11548-013-0932-5. Epub 2013 Jul 31. Int J Comput Assist Radiol Surg. 2014. PMID: 23900851
-
Reconstruction of knee anatomy from single-plane fluoroscopic x-ray based on a nonlinear statistical shape model.J Med Imaging (Bellingham). 2021 Jan;8(1):016001. doi: 10.1117/1.JMI.8.1.016001. Epub 2021 Jan 11. J Med Imaging (Bellingham). 2021. PMID: 33457444 Free PMC article.
-
Intraoperative image-based multiview 2D/3D registration for image-guided orthopaedic surgery: incorporation of fiducial-based C-arm tracking and GPU-acceleration.IEEE Trans Med Imaging. 2012 Apr;31(4):948-62. doi: 10.1109/TMI.2011.2176555. Epub 2011 Nov 18. IEEE Trans Med Imaging. 2012. PMID: 22113773 Free PMC article.
-
An Experimental Study of a 3D Bone Position Estimation System Based on Fluoroscopic Images.Diagnostics (Basel). 2022 Sep 16;12(9):2237. doi: 10.3390/diagnostics12092237. Diagnostics (Basel). 2022. PMID: 36140638 Free PMC article.
-
Prediction of in vivo knee joint kinematics using a combined dual fluoroscopy imaging and statistical shape modeling technique.J Biomech Eng. 2014 Dec;136(12):124503. doi: 10.1115/1.4028819. J Biomech Eng. 2014. PMID: 25320846 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources