Fast quasi-automated 3D reconstruction of lower limbs from low dose biplanar radiographs using statistical shape models and contour matching

Gajny, Laurent; Girinon, François; Bayoud, Wael; Lahkar, Bhrigu Kumar; Bonnet-Lebrun, Aurore; Rouch, Philippe; Lazennec, Jean-Yves; Skalli, Wafa

doi:10.1016/j.medengphy.2022.103769

Cited by 5 publications

(3 citation statements)

References 18 publications

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“…After the initial screening of abstracts, the full text of 75 records were analysed (Figure 2). Following full‐text review, 34 studies were included for final data extraction 15–48 …”

Section: Resultsmentioning

confidence: 99%

“…It is noteworthy that the distal femur was a commonly modelled bone, with 12 separate publications. 15,16,20,24,25,27,31,38,39,41,42,48 A likely reason for this is the role of patient specific instrumentation (PSI) in knee replacement (TKR) surgery. PSI is a technique designed to improve overall surgical accuracy during prosthesis insertion.…”

Section: Risk Of Bias (Table 6)mentioning

confidence: 99%

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The accuracy of statistical shape models in predicting bone shape: A systematic review

Patil

Kulkarni

Xie

et al. 2023

Robotics Computer Surgery

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Background This systematic review aims to ascertain how accurately 3D models can be predicted from two‐dimensional (2D) imaging utilising statistical shape modelling. Methods A systematic search of published literature was conducted in September 2022. All papers which assessed the accuracy of 3D models predicted from 2D imaging utilising statistical shape models and which validated the models against the ground truth were eligible. Results 2127 papers were screened and a total of 34 studies were included for final data extraction. The best overall achievable accuracy was 0.45 mm (root mean square error) and 0.16 mm (average error). Conclusion Statistical shape modelling can predict detailed 3D anatomical models from minimal 2D imaging. Future studies should report the intended application domain of the model, the level of accuracy required, the underlying demographics of subjects, and the method in which accuracy was calculated, with root mean square error recommended if appropriate.

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“…After the initial screening of abstracts, the full text of 75 records were analysed (Figure 2). Following full‐text review, 34 studies were included for final data extraction 15–48 …”

Section: Resultsmentioning

confidence: 99%

Section: Risk Of Bias (Table 6)mentioning

confidence: 99%

The accuracy of statistical shape models in predicting bone shape: A systematic review

Patil

Kulkarni

Xie

et al. 2023

Robotics Computer Surgery

View full text Add to dashboard Cite

show abstract

“…10 A volumetric skeletal image, such as CT, is utilized to generate DRR for 2D-3D registration, but its acquisition requires cost and time exposing subjects to radiation. 22 Previous 2D-3D registration studies utilized a statistical shape model (SSM), 23,24 a deformable surface mesh model, to perform 2D-3D registration and skeletal model estimation simultaneously. The SSM represents variations in anatomical structures within the population in a training dataset.…”

Section: Introductionmentioning

confidence: 99%