Validation of phalanx bone three-dimensional surface segmentation from computed tomography images using laser scanning

DeVries, Nicole A.; Gassman, Esther E.; Kallemeyn, Nicole A.; Shivanna, Kiran H.; Magnotta, Vincent A.; Grosland, Nicole M.

doi:10.1007/s00256-007-0386-3

Cited by 29 publications

(31 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The bony edges were outlined and used to reconstruct the 3D models of the femur and tibia. The accuracy of the 3D models was estimated at 0.4 mm according to the imaging resolution (DeVries et al, 2008). …”

Section: Methodsmentioning

confidence: 99%

In-vivo analysis of flexion axes of the knee: Femoral condylar motion during dynamic knee flexion

Tsai

Rubash

et al. 2016

Clinical Biomechanics

View full text Add to dashboard Cite

Background Transepicondylar axis and geometrical center axis are widely used for investigation of the knee kinematics and component alignment in total knee arthroplasty. However, the kinematic characteristics of these knee axes are not well defined in literature. This study investigated the femoral condylar motion during a dynamic flexion of the knee using different flexion axes. Methods Twenty healthy knees (10 males and 10 females) were CT scanned to create 3D anatomic models. The subjects performed a single leg flexion from full extension to maximal flexion while the knees were imaged using fluoroscopes. The femoral condyle translations in anterior-posterior and proximal-distal directions were described using clinical transepicondylar axis, surgical transepicondylar axis and geometrical center axis. Findings The subjects achieved −9.4° (SD 3.0°) hyperextension at full extension and 116.4° (SD 9.0°) at maximal flexion of the knee. The anterior-posterior translations of the three flexion axes were different for the medial condyle, but similar for the lateral condyle. Substantial variations of the condylar motion in proximal-distal direction were measured along the flexion path using these axes. While the surgical transepicondylar axis maintained condyle heights from full extension to 60° of flexion, geometrical center axis showed little changes in condyle heights from 30° to maximal knee flexion. The condyles moved distally beyond 90° flexion using both transepicondylar axes. Interpretation The femoral condylar motion measurement is sensitive to the selection of flexion axis. The different kinematic features of these axes provide an insightful reference when selecting a flexion axis in total knee arthroplasty component alignment.

show abstract

Section: Methodsmentioning

confidence: 99%

In-vivo analysis of flexion axes of the knee: Femoral condylar motion during dynamic knee flexion

Tsai

Rubash

et al. 2016

Clinical Biomechanics

View full text Add to dashboard Cite

show abstract

“…The relative overlap computed between the two raters was 0.89 for all the bones. The individual bones, the proximal, middle, and distal phalanges, had relative overlaps of 0.91, 0.90, and 0.87, respectively (19). …”

Section: Methodsmentioning

confidence: 99%

Semi-automated Phalanx Bone Segmentation Using the Expectation Maximization Algorithm

et al. 2008

Self Cite

View full text Add to dashboard Cite

Medical imaging technologies have allowed for in vivo exploration and evaluation of the human musculoskeletal system. Three-dimensional bone models generated using image segmentation techniques provide a means to optimize individualized orthopaedic surgical procedures using engineering analyses. However, many of the current segmentation techniques are not clinically practical due to the required time and human intervention. As a proof of concept, we demonstrate the use of an expectation maximization (EM) algorithm to segment the hand phalanx bones, and hypothesize that this semi-automated technique will improve on the efficiency while providing similar definitions as compared to a manual rater. Our results show a relative overlap of the proximal, middle, and distal phalanx bones of 0.83, 0.79, and 0.72 for the EM technique when compared to validated manual segmentations. The EM segmentations were also compared to 3D surface scans of the cadaveric specimens, which resulted in distance maps showing an average distance for the proximal, middle, and distal phalanx bones of 0.45, 0.46, and 0.51 mm, respectively. The EM segmentation improved on the segmentation speed of the manual techniques by a factor of eight. Overall, the manual segmentations had greater relative overlap metric values, which suggests that the manual segmentations are a better fit to the actual surface of the bone. As shown by the comparison to the bone surface scans, the EM technique provides a similar representation of the anatomic structure and offers an increase in efficiency that could help to reduce the time needed for defining anatomical structures from CT scans.

show abstract

“…The process of delineating the anatomic structures can be performed via a variety of techniques including manual, semi-automated, and fully automated techniques. The ability to define geometrically accurate representations of bony structures has previously been studied by DeVries et al[21] While defining the phalanx bones of the hand, good agreement was found between manual raters (Jaccard metric = 0.91) and physical laser scans of the same specimens (surface distance = 0.20mm). To facilitate the creation of the anatomic models both semi-automated techniques such as the expectation-maximization algorithms [16] as well as artificial neural networks (ANNs)[17] have been explored.…”

Section: Surgical Simulation Techniquesmentioning

confidence: 99%

Toward the Development of Virtual Surgical Tools to Aid Orthopaedic FE Analyses

Tadepalli

Shivanna

Magnotta

et al. 2009

EURASIP J. Adv. Signal Process.

Self Cite

View full text Add to dashboard Cite

Computational models of joint anatomy and function provide a means for biomechanists, physicians, and physical therapists to understand the effects of repetitive motion, acute injury, and degenerative diseases. Finite element models, for example, may be used to predict the outcome of a surgical intervention or to improve the design of prosthetic implants. Countless models have been developed over the years to address a myriad of orthopaedic procedures. Unfortunately, few studies have incorporated patient-specific models. Historically, baseline anatomic models have been used due to the demands associated with model development. Moreover, surgical simulations impose additional modeling challenges. Current meshing practices do not readily accommodate the inclusion of implants. Our goal is to develop a suite of tools (virtual instruments and guides) which enable surgical procedures to be readily simulated and to facilitate the development of all-hexahedral finite element mesh definitions.

show abstract

Validation of phalanx bone three-dimensional surface segmentation from computed tomography images using laser scanning

Cited by 29 publications

References 25 publications

In-vivo analysis of flexion axes of the knee: Femoral condylar motion during dynamic knee flexion

In-vivo analysis of flexion axes of the knee: Femoral condylar motion during dynamic knee flexion

Semi-automated Phalanx Bone Segmentation Using the Expectation Maximization Algorithm

Toward the Development of Virtual Surgical Tools to Aid Orthopaedic FE Analyses

Contact Info

Product

Resources

About