A personalized ellipsoid modeling method and matching error analysis for the artificial femoral head design

Liu, Bin; Hua, Shungang; Zhang, Hui; Liu, Zhaoliang; Xu, Zhao‐Dong; Zhang, Bingbing; Yue, Zongge

doi:10.1016/j.cad.2014.06.009

Cited by 7 publications

(4 citation statements)

References 38 publications

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“…Although his classification has been known for over 40 years, many computer-aided orthopedic surgery methodologies still remain faithful to the spherical classification. On the other hand, several studies have considered nonspherical shapes but none were truly ovoidal [4][5][6][7][8][9][10][11][12][13][14][15]. Generic ovoidal shapes could contribute significantly to the anatomical description of human joints and to design improved artificial joints.…”

Section: Discussionmentioning

confidence: 99%

“…For spheroidal articular surfaces, such as the humeral and femoral heads, the standard classification regarding shape modeling is that these surfaces can be represented by spherical shapes [1][2][3]. Despite this classification, several authors within the orthopedic surgery and prosthetic design communities have noted that the femoral head and acetabular cavity are not clearly spherical, but are actually more complex in shape exhibiting quasihomogeneous curvatures [4][5][6][7][8][9][10][11][12][13][14][15][16]. Most of these studies use spheres and ellipsoids to describe the shapes [4][5][6][7][8][9][10][11], although some consider conchoids [4,7,15].…”

Section: Introductionmentioning

confidence: 99%

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Shape Analysis of the Femoral Head: A Comparative Study Between Spherical, (Super)Ellipsoidal, and (Super)Ovoidal Shapes

Lopes

Neptune

Gonçalves

et al. 2015

Journal of Biomechanical Engineering

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In this work, MacConaill's classification that the articular surface of the femoral head is better represented by ovoidal shapes rather than purely spherical shapes is computationally tested. To test MacConaill's classification, a surface fitting framework was developed to fit spheres, ellipsoids, superellipsoids, ovoids, and superovoids to computed tomography (CT) data of the femoral proximal epiphysis. The framework includes several image processing and computational geometry techniques, such as active contour segmentation and mesh smoothing, where implicit surface fitting is performed with genetic algorithms. By comparing the surface fitting error statistics, the results indicate that (super)ovoids fit femoral articular surfaces better than spherical or (super)ellipsoidal shapes.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Shape Analysis of the Femoral Head: A Comparative Study Between Spherical, (Super)Ellipsoidal, and (Super)Ovoidal Shapes

Lopes

Neptune

Gonçalves

et al. 2015

Journal of Biomechanical Engineering

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show abstract

“…These and other considerations have fostered the research on alternative methods for incorporating uncertainty in the structural analysis, such as fuzzy sets and related theories [95], anti-optimization or convex-set modeling [96], interval analysis [97], random sets [98], ellipsoid modeling [99,100] and worstcase scenarios [101]. Comparisons have been also made between probabilistic and alternative methods [102] or their combination has been explored [103,104].…”

Section: The Methods Of Reliability Theory Of Building Construction Imentioning

confidence: 99%

A new approach to the design of suspension roof systems

Priadko

Rudnіeva

Ribakov

et al. 2020

OMTC

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Over the last century, the suspension roofs design has progressed until the advent of the shells theory in the first half of the 20th century, due to a rapid pace in technological advancement. A paradigm shift emerged with the new trend in structural design towards a new design process that cooperatively integrated economy, efficiency, and elegance. Different approaches in computation, design and reliability assessment of roof structures are discussed in this work to identify the key conditions that have significantly contributed to modern suspension roof design principles. A new algorithm to assess the reliability of suspension roofs at the design stage is proposed and a novel method for computational design and reliability evaluation of suspension roofs is presented in this paper. This method enables to solve some topical issues, such as assignment of initial geometric roof parameters and relevant problems, like numerical determination of reliability indices for statistically non-determined systems of suspension roofs with a big cut on elliptical plan.

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“…Clinically, the proposed thickness measurement is more likely to be applicable for the hip joint with the spherical-like femoral head, which could be in early and/or less severe OA conditions without bony deformities of the femoral head. For the hip joint with the non-spherical femoral head such as in more severe OA states, a more dedicated model for the femoral head, e.g., an ellipsoid model (Liu et al 2014), will be needed to reduce the potential measurement errors.…”

Section: Discussionmentioning

confidence: 99%

Automated segmentation and quantitative analysis of the hip joint from magnetic resonance images

Xia¹

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The aim of this thesis is to develop a novel computer-aided system with advanced medical image processing approaches. This will allow automatic segmentation and quantification of the osteochondral elements (i.e. the articulating bones and cartilages) from high-resolution three-dimensional (3D) magnetic resonance (MR) images of the hip joint.This research is motivated by the importance of early detection of structural changes and degeneration of the bones and articular cartilages for good patient outcomes, particularly for early and pre-osteoarthritic conditions such as cam-type femoroacetabular impingement (FAI). MR imaging provides an optimal tool for in vivo assessment of the hip joint structure, including the bones and cartilages. This has generated extensive interest in the development of MR technologies to analyse cartilage morphology and assess biochemical compositions of the hyaline cartilage to facilitate early diagnostic and treatment for hip osteoarthritis (OA) and FAI.Quantitative analyses can provide useful morphometric data from complex MR data. In the hip joint, the segmentation of bones and cartilages is an essential prerequisite, which must be accurate, reliable and reproducible, for quantitative measurements. However, this is difficult and is traditionally performed using time-and expert-intensive manual or semi-automatic methods.The hypothesis behind this research is that accurate and reproducible quantitative data can be automatically obtained from high-resolution 3D MR images of the hip joint, through the use of advanced image processing techniques. To this end, this research focuses on two specific aims: Aim 1 -to develop and evaluate a fully automated segmentation approach to deliver accurate and reproducible bone and cartilage segmentations from high-resolution 3D MR images of the hip joint and Aim 2 -to automatically extract reliable and reproducible morphometric data based on the segmented subchondral bones and articular cartilages.The development of an automatic segmentation scheme for the bones and cartilages with high precision and reproducibility is firstly needed in order to provide a basis for subsequent quantitative measurements, which deliver reliable morphometric data of the segmented bones and cartilages for the use in early OA and FAI studies. To attain these aims, images were acquired using different MR sequences from a mixed demographic (male or female and young adult to elderly) of participants with a variety of femoral head-neck junction presentations but no apparent hip OA. Different sequence scans were used to image the same participant for the associated reproducibility experiments.Two state-of-the-art methods (multi-atlas-based and active shape model (ASM) based algorithms) i were developed and evaluated for automatic segmentation of proximal femurs and innominate bones from large field of view (FOV) MR images (water-excitation dual echo steady state (DESS) and multi echo data image combination (MEDIC)). The validation results have indicated accurate and robust...

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A personalized ellipsoid modeling method and matching error analysis for the artificial femoral head design

Cited by 7 publications

References 38 publications

Shape Analysis of the Femoral Head: A Comparative Study Between Spherical, (Super)Ellipsoidal, and (Super)Ovoidal Shapes

Shape Analysis of the Femoral Head: A Comparative Study Between Spherical, (Super)Ellipsoidal, and (Super)Ovoidal Shapes

A new approach to the design of suspension roof systems

Automated segmentation and quantitative analysis of the hip joint from magnetic resonance images

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