3D Elbow Kinematics with Monoplanar Fluoroscopy: In Silico Evaluation

Tersi, Luca; Fantozzi, Silvia; Stagni, Rita

doi:10.1155/2010/142989

Cited by 7 publications

(13 citation statements)

References 44 publications

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“…This method has proved effective for assessing in vivo kinematics of joint prostheses, including that of the hip [29,30], knee [32-34, 51, 55], and ankle [38], due to the high contrast at the edges of the metal implant. Joint kinematics has also been measured in natural joints including the elbow [27] and lumbar spine [44] using bone-edge information. In general, however, because bones have smooth, rounded contours and are covered by varying amounts of soft tissue, feature detection in natural joints may be problematic.…”

Section: State-of-the-art In X-ray Fluoroscopymentioning

confidence: 99%

Future trends in the use of X-ray fluoroscopy for the measurement and modelling of joint motion

Ackland

Keynejad

Pandy

2011

Proc Inst Mech Eng H

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Knowledge of three-dimensional skeletal kinematics during functional activities such as walking, is required for accurate modelling of joint motion and loading, and is important in identifying the effects of injury and disease. For example, accurate measurement of joint kinematics is essential in understanding the pathogenesis of osteoarthritis and its symptoms and for developing strategies to alleviate joint pain. Bi-plane X-ray fluoroscopy has the capacity to accurately and non-invasively measure human joint motion in vivo. Joint kinematics obtained using bi-plane X-ray fluoroscopy will aid in the development of more complex musculoskeletal models, which may be used to assess joint function and disease and plan surgical interventions and post-operative rehabilitation strategies. At present, however, commercial C-arm systems constrain the motion of the subject within the imaging field of view, thus precluding recording of motions such as overground gait. These fluoroscopy systems also operate at low frame rates and therefore cannot accurately capture high-speed joint motion during tasks such as running and throwing. In the future, bi-plane fluoroscopy systems may include computer-controlled tracking for the measurement of joint kinematics over entire cycles of overground gait without constraining motion of the subject. High-speed cameras will facilitate measurement of high-impulse joint motions, and computationally efficient pose-estimation software may provide a fast and fully automated process for quantification of natural joint motion.

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Section: State-of-the-art In X-ray Fluoroscopymentioning

confidence: 99%

Future trends in the use of X-ray fluoroscopy for the measurement and modelling of joint motion

Ackland

Keynejad

Pandy

2011

Proc Inst Mech Eng H

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“…However, advances in computer-aided design (CAD) and some automatic algorithms have hastened the development of the model-based RSA technique [11,17]. Furthermore, some studies developed kinematic estimation and optimization algorithm of knees to increase accuracy and precision with single-plane fluoroscopy [16,[19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Predicting 3D pose in partially overlapped X-ray images of knee prostheses using model-based Roentgen stereophotogrammetric analysis (RSA)

Hsu

Lin

Shih

et al. 2014

Med Biol Eng Comput

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After total knee replacement, the model-based Roentgen stereophotogrammetric analysis (RSA) technique has been used to monitor the status of prosthetic wear, misalignment, and even failure. However, the overlap of the prosthetic outlines inevitably increases errors in the estimation of prosthetic poses due to the limited amount of available outlines. In the literature, quite a few studies have investigated the problems induced by the overlapped outlines, and manual adjustment is still the mainstream. This study proposes two methods to automate the image processing of overlapped outlines prior to the pose registration of prosthetic models. The outline-separated method defines the intersected points and segments the overlapped outlines. The feature-recognized method uses the point and line features of the remaining outlines to initiate registration. Overlap percentage is defined as the ratio of overlapped to non-overlapped outlines. The simulated images with five overlapping percentages are used to evaluate the robustness and accuracy of the proposed methods. Compared with non-overlapped images, overlapped images reduce the number of outlines available for model-based RSA calculation. The maximum and root mean square errors for a prosthetic outline are 0.35 and 0.04 mm, respectively. The mean translation and rotation errors are 0.11 mm and 0.18°, respectively. The errors of the model-based RSA results are increased when the overlap percentage is beyond about 9%. In conclusion, both outline-separated and feature-recognized methods can be seamlessly integrated to automate the calculation of rough registration. This can significantly increase the clinical practicability of the model-based RSA technique.

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“…As a result, 3DF optimization landscape is characterized by a small global optimum attraction basin of approximately 3 mm and 3 • surrounded by local optima and flat areas [21].…”

mentioning

confidence: 99%

“…Lavallée and Szelinsky [22] proposed the Levenberg-Marquardt optimization algorithm (LMA), a maximum neighborhood method performing an optimum interpolation between the Gauss-Newton and the Steepest-Descent methods [23]. Since it is extremely fast, LMA was intensively used [21], [24]- [26], but its performance is too sensitive to local optima and flat areas not providing information for the optimization algorithm convergence [21]. Therefore, in 3DF, gradient-based methods such as LMA are highly dependent on the initial pose estimate, which is typically specified manually [21].…”

mentioning

confidence: 99%

“…Since it is extremely fast, LMA was intensively used [21], [24]- [26], but its performance is too sensitive to local optima and flat areas not providing information for the optimization algorithm convergence [21]. Therefore, in 3DF, gradient-based methods such as LMA are highly dependent on the initial pose estimate, which is typically specified manually [21]. As a consequence of its residual operator-dependency [14] and concomitant cumbersome application, the use of 3DF kinematics quantification in routine clinical practice has been hindered.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Characterization of the Performance of Memetic Algorithms for the Automation of Bone Tracking With Fluoroscopy

Tersi

Fantozzi

Stagni

2015

IEEE Trans. Evol. Computat.

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Reliable knowledge of in vivo joint kinematics is fundamental in clinical medicine. Fluoroscopic motion tracking theoretically permits a millimeter/degree level of accuracy in 3-D joint motion analysis, but the reliability of the local optimization algorithm [Levenberg-Marquardt (LMA)], typically used for the pose estimation, is highly operator dependent. A new memetic algorithm (MA), hybridizing global evolution and a local search metaphor for learning, is proposed to automate the analysis and improve its reliability and robustness. The performance of MA was assessed for in silico and in vivo elbow kinematics, with and without user supervision. The best learning strategy between Lamarckian and Baldwinian evolution was identified. MA's accuracy and repeatability was quantified and compared with LMA's. The algorithm performed best using a partial Lamarckian learning strategy. The geometric symmetry of analyzed bony segments influenced the accuracy, whereas the absolute bone pose with respect to the projection geometry affected the repeatability. In contrast to LMA, MA provided robust, repeatable, and operator independent pose estimations, even for in vivo analyses. The pose can be automatically estimated with errors lower than 1 mm and 1 • for all the pose parameters except the depth position, if the investigated motion task avoids symmetric bony projection silhouettes.

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3D Elbow Kinematics with Monoplanar Fluoroscopy: In Silico Evaluation

Cited by 7 publications

References 44 publications

Future trends in the use of X-ray fluoroscopy for the measurement and modelling of joint motion

Future trends in the use of X-ray fluoroscopy for the measurement and modelling of joint motion

Predicting 3D pose in partially overlapped X-ray images of knee prostheses using model-based Roentgen stereophotogrammetric analysis (RSA)

Characterization of the Performance of Memetic Algorithms for the Automation of Bone Tracking With Fluoroscopy

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