Registration Algorithm for Statistical Bone Shape Reconstruction from Radiographs - An Accuracy Study

Gollmer, Sebastian T.; Lachner, Rainer; Buzug, Thorsten M.

doi:10.1109/iembs.2007.4353814

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…These methods align a 3D bone model, segmented from CT or MRI, with calibrated fluoroscopic sequences. Alignment is achieved by minimizing either an image intensity distance through calculation of digitally reconstructed radiographs (DRR) (Anderst et al, 2009; Bey et al, 2008; Dennis et al, 2005; Mahfouz et al, 2003; Muhit et al, 2010; Nakajima et al, 2007; Pickering et al, 2009; Scott and Barney Smith, 2006; You et al, 2001), or an image edge to bone model silhouette distance (Defrate et al, 2006; Fregly et al, 2005; Gollmer et al, 2007; Hanson et al, 2006; Hirokawa et al, 2008; Kitagawa et al, 2010; Li et al, 2008; Tersi et al, 2012; Torry et al, 2011; Tsai et al, 2010). Kinematic analysis not requiring the subject-specific 3D model would, however, be preferred, as it would lower analysis costs and eliminate the prior 3D acquisition resulting in lower radiation dose in the case of CT.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of automated statistical shape model based knee kinematics from biplane fluoroscopy

Baka

Kaptein

Giphart

et al. 2014

Journal of Biomechanics

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State-of-the-art fluoroscopic knee kinematic analysis methods require the patient-specific bone shapes segmented from CT or MRI. Substituting the patient-specific bone shapes with personalizable models, such as statistical shape models (SSM), could eliminate the CT/MRI acquisitions, and thereby decrease costs and radiation dose (when eliminating CT). SSM based kinematics, however, have not yet been evaluated on clinically relevant joint motion parameters. Therefore, in this work the applicability of SSM-s for computing knee kinematics from biplane fluoroscopic sequences was explored. Kinematic precision with an edge based automated bone tracking method using SSM-s was evaluated on 6 cadaver and 10 in-vivo fluoroscopic sequences. The SSMs of the femur and the tibia-fibula were created using 61 training datasets. Kinematic precision was determined for medial-lateral tibial shift, anterior-posterior tibial drawer, joint distraction-contraction, flexion, tibial rotation and adduction. The relationship between kinematic precision and bone shape accuracy was also investigated. The SSM based kinematics resulted in sub-millimeter (0.48–0.81 mm) and approximately one degree (0.69–0.99°) median precision on the cadaveric knees compared to bone-marker-based kinematics. The precision on the in-vivo datasets was comparable to the cadaveric sequences when evaluated with a semi-automatic reference method. These results are promising, though further work is necessary to reach the accuracy of CT-based kinematics. We also demonstrated that a better shape reconstruction accuracy does not automatically imply a better kinematic precision. This result suggests that the ability of accurately fitting the edges in the fluoroscopic sequences has a larger role in determining the kinematic precision than the overall 3D shape accuracy.

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Section: Introductionmentioning

confidence: 99%

Evaluation of automated statistical shape model based knee kinematics from biplane fluoroscopy

Baka

Kaptein

Giphart

et al. 2014

Journal of Biomechanics

View full text Add to dashboard Cite

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Statistical shape modeling predicts patellar bone geometry to enable stereo-radiographic kinematic tracking

Smoger

Shelburne

Cyr

et al. 2017

Journal of Biomechanics

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Complications in the patellofemoral (PF) joint of patients with total knee replacements include patellar subluxation and dislocation, and remain a cause for revision. Kinematic measurements to assess these complications and evaluate implant designs require the accuracy of dynamic stereo-radiographic systems with 3D-2D registration techniques. While tibiofemoral kinematics are typically derived by tracking metallic implants, PF kinematic measurements are difficult as the patellar implant is radiotransparent and a representation of the resected patella bone requires either pre-surgical imaging and precise implant placement or post-surgical imaging. Statistical shape models (SSMs), used to characterize anatomic variation, provide an alternative means to obtain the representation of the resected patella for use in kinematic tracking. Using a virtual platform of a stereo-radiographic system, the objectives of this study were to evaluate the ability of an SSM to predict subject-specific 3D implanted patellar geometries from simulated 2D image profiles, and to formulate an effective data collection methodology for PF kinematics by considering accuracy for a variety of patient pose scenarios. An SSM of the patella was developed for 50 subjects and a leave-one-out approach compared SSM-predicted and actual geometries; average 3D errors were 0.45±0.07 mm (mean ± standard deviation), which is comparable to the accuracy of traditional segmentation. Further, initial imaging of the patella in five unique stereo radiographic perspectives yielded the most accurate representation. The ability to predict the remaining patellar geometry of the implanted PF joint with radiographic images and SSM, instead of CT, can reduce radiation exposure and streamline in vivo kinematic evaluations.

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Registration Algorithm for Statistical Bone Shape Reconstruction from Radiographs - An Accuracy Study

Cited by 2 publications

References 7 publications

Evaluation of automated statistical shape model based knee kinematics from biplane fluoroscopy

Evaluation of automated statistical shape model based knee kinematics from biplane fluoroscopy

Statistical shape modeling predicts patellar bone geometry to enable stereo-radiographic kinematic tracking

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