Literature DB >> 22206419

Static and dynamic error of a biplanar videoradiography system using marker-based and markerless tracking techniques.

Daniel L Miranda1, Joel B Schwartz, Andrew C Loomis, Elizabeth L Brainerd, Braden C Fleming, Joseph J Crisco.   

Abstract

The use of biplanar videoradiography technology has become increasingly popular for evaluating joint function in vivo. Two fundamentally different methods are currently employed to reconstruct 3D bone motions captured using this technology. Marker-based tracking requires at least three radio-opaque markers to be implanted in the bone of interest. Markerless tracking makes use of algorithms designed to match 3D bone shapes to biplanar videoradiography data. In order to reliably quantify in vivo bone motion, the systematic error of these tracking techniques should be evaluated. Herein, we present new markerless tracking software that makes use of modern GPU technology, describe a versatile method for quantifying the systematic error of a biplanar videoradiography motion capture system using independent gold standard instrumentation, and evaluate the systematic error of the W.M. Keck XROMM Facility's biplanar videoradiography system using both marker-based and markerless tracking algorithms under static and dynamic motion conditions. A polycarbonate flag embedded with 12 radio-opaque markers was used to evaluate the systematic error of the marker-based tracking algorithm. Three human cadaveric bones (distal femur, distal radius, and distal ulna) were used to evaluate the systematic error of the markerless tracking algorithm. The systematic error was evaluated by comparing motions to independent gold standard instrumentation. Static motions were compared to high accuracy linear and rotary stages while dynamic motions were compared to a high accuracy angular displacement transducer. Marker-based tracking was shown to effectively track motion to within 0.1 mm and 0.1 deg under static and dynamic conditions. Furthermore, the presented results indicate that markerless tracking can be used to effectively track rapid bone motions to within 0.15 deg for the distal aspects of the femur, radius, and ulna. Both marker-based and markerless tracking techniques were in excellent agreement with the gold standard instrumentation for both static and dynamic testing protocols. Future research will employ these techniques to quantify in vivo joint motion for high-speed upper and lower extremity impacts such as jumping, landing, and hammering.

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Mesh:

Year:  2011        PMID: 22206419      PMCID: PMC3267989          DOI: 10.1115/1.4005471

Source DB:  PubMed          Journal:  J Biomech Eng        ISSN: 0148-0731            Impact factor:   2.097


  33 in total

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Journal:  Med Sci Sports Exerc       Date:  2011-03       Impact factor: 5.411

2.  Model-based tracking of the hip: implications for novel analyses of hip pathology.

Authors:  Daniel E Martin; Nicholas J Greco; Brian A Klatt; Vonda J Wright; William J Anderst; Scott Tashman
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3.  Biomechanical measures of neuromuscular control and valgus loading of the knee predict anterior cruciate ligament injury risk in female athletes: a prospective study.

Authors:  Timothy E Hewett; Gregory D Myer; Kevin R Ford; Robert S Heidt; Angelo J Colosimo; Scott G McLean; Antonie J van den Bogert; Mark V Paterno; Paul Succop
Journal:  Am J Sports Med       Date:  2005-02-08       Impact factor: 6.202

4.  A comparison of dynamic coronal plane excursion between matched male and female athletes when performing single leg landings.

Authors:  Kevin R Ford; Gregory D Myer; Rose L Smith; Rebecca M Vianello; Shelly L Seiwert; Timothy E Hewett
Journal:  Clin Biomech (Bristol, Avon)       Date:  2005-09-28       Impact factor: 2.063

5.  Validation of a new model-based tracking technique for measuring three-dimensional, in vivo glenohumeral joint kinematics.

Authors:  Michael J Bey; Roger Zauel; Stephanie K Brock; Scott Tashman
Journal:  J Biomech Eng       Date:  2006-08       Impact factor: 2.097

6.  Measuring dynamic in-vivo glenohumeral joint kinematics: technique and preliminary results.

Authors:  Michael J Bey; Stephanie K Kline; Roger Zauel; Terrence R Lock; Patricia A Kolowich
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7.  X-ray reconstruction of moving morphology (XROMM): precision, accuracy and applications in comparative biomechanics research.

Authors:  Elizabeth L Brainerd; David B Baier; Stephen M Gatesy; Tyson L Hedrick; Keith A Metzger; Susannah L Gilbert; Joseph J Crisco
Journal:  J Exp Zool A Ecol Genet Physiol       Date:  2010-06-01

8.  Automatic determination of anatomical coordinate systems for three-dimensional bone models of the isolated human knee.

Authors:  Daniel L Miranda; Michael J Rainbow; Evan L Leventhal; Joseph J Crisco; Braden C Fleming
Journal:  J Biomech       Date:  2010-02-18       Impact factor: 2.712

9.  Comments on "validation of a non-invasive fluoroscopic imaging technique for the measurement of dynamic knee joint motion".

Authors:  Scott Tashman
Journal:  J Biomech       Date:  2008-10-18       Impact factor: 2.712

10.  Accuracy of biplane x-ray imaging combined with model-based tracking for measuring in-vivo patellofemoral joint motion.

Authors:  Michael J Bey; Stephanie K Kline; Scott Tashman; Roger Zauel
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  40 in total

1.  Quantifying cross-scatter contamination in biplane fluoroscopy motion analysis systems.

Authors:  Janelle A Cross; Ben McHenry; Taly Gilat Schmidt
Journal:  J Med Imaging (Bellingham)       Date:  2015-10-23

2.  Assessment of Knee Kinematics in Older Adults Using High-Speed Stereo Radiography.

Authors:  Vasiliki Kefala; Adam J Cyr; Michael D Harris; Donald R Hume; Bradley S Davidson; Raymond H Kim; Kevin B Shelburne
Journal:  Med Sci Sports Exerc       Date:  2017-11       Impact factor: 5.411

3.  Accuracy of biplane videoradiography for quantifying dynamic wrist kinematics.

Authors:  Bardiya Akhbari; Amy M Morton; Douglas C Moore; Arnold-Peter C Weiss; Scott W Wolfe; Joseph J Crisco
Journal:  J Biomech       Date:  2019-05-29       Impact factor: 2.712

4.  A technique for quantifying wrist motion using four-dimensional computed tomography: approach and validation.

Authors:  Kristin Zhao; Ryan Breighner; David Holmes; Shuai Leng; Cynthia McCollough; Kai-Nan An
Journal:  J Biomech Eng       Date:  2015-06-03       Impact factor: 2.097

5.  A computationally efficient strategy to estimate muscle forces in a finite element musculoskeletal model of the lower limb.

Authors:  Alessandro Navacchia; Donald R Hume; Paul J Rullkoetter; Kevin B Shelburne
Journal:  J Biomech       Date:  2018-12-28       Impact factor: 2.712

6.  A platform for semiautomated voluntary training of common marmosets for behavioral neuroscience.

Authors:  Jeffrey D Walker; Friederice Pirschel; Nicholas Gidmark; Jason N MacLean; Nicholas G Hatsopoulos
Journal:  J Neurophysiol       Date:  2020-03-04       Impact factor: 2.714

7.  In vitro quantification of the performance of model-based mono-planar and bi-planar fluoroscopy for 3D joint kinematics estimation.

Authors:  Luca Tersi; Arnaud Barré; Silvia Fantozzi; Rita Stagni
Journal:  Med Biol Eng Comput       Date:  2012-11-11       Impact factor: 2.602

8.  Comparison of Marker-Based and Stereo Radiography Knee Kinematics in Activities of Daily Living.

Authors:  Donald R Hume; Vasiliki Kefala; Michael D Harris; Kevin B Shelburne
Journal:  Ann Biomed Eng       Date:  2018-06-14       Impact factor: 3.934

9.  Dependence of Muscle Moment Arms on In Vivo Three-Dimensional Kinematics of the Knee.

Authors:  Alessandro Navacchia; Vasiliki Kefala; Kevin B Shelburne
Journal:  Ann Biomed Eng       Date:  2016-09-12       Impact factor: 3.934

10.  The effect of modified Broström-Gould repair for lateral ankle instability on in vivo tibiotalar kinematics.

Authors:  William B Wainright; Charles E Spritzer; Jun Young Lee; Mark E Easley; James K DeOrio; James A Nunley; Louis E DeFrate
Journal:  Am J Sports Med       Date:  2012-08-10       Impact factor: 6.202

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