Non-Linear Filtering Technique Used for Testing the Human Lumbar Spine FEA Model

Punarselvam, E.; Ponnan, Suresh

doi:10.1007/s10916-018-1148-6

Cited by 7 publications

(6 citation statements)

References 32 publications

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“…The primary input for the FEM software (ANSYS) lumbar spine model geometrical generation was these coordinate files. The other geometrical parameters to build the model were calculated from these initial sagittal parameters and geometrical relationships derived from different published studies. ,, The mesh density was crucial because the thicker the density the more accurate the calculations were, and the computation time was also longer.…”

Section: Methodsmentioning

confidence: 99%

“… 13 It has limitations as a computer simulation study but it is easy to use and mimics different clinical scenarios. 14 …”

Section: Introductionmentioning

confidence: 99%

“…13 It has limitations as a computer simulation study but it is easy to use and mimics different clinical scenarios. 14 We aimed to assess with a lumbar spine parametric FEM a new ring-shaped nucleus implant made of a polymeric material (Bionate 80A, The Polymer Technology Group DSM-PTG, Berkeley, California). 15 Under different loading conditions, we analyzed implant mechanical responses and interactions between operated discs and surrounding anatomical structures, such as spinal ligaments, annulus, end plates, and facet joints.…”

Section: Introductionmentioning

confidence: 99%

“…This methodology allows implant design evaluation before manufacturing, cost savings, design improvement, and future optimizations . It has limitations as a computer simulation study but it is easy to use and mimics different clinical scenarios …”

Section: Introductionmentioning

confidence: 99%

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Finite Element Analysis of a Bionate Ring-Shaped Customized Lumbar Disc Nucleus Prosthesis

Vanaclocha

Atienza

et al. 2021

ACS Appl. Bio Mater.

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Study design : Biomechanical study of a nucleus replacement with a finite element model. Objective : To validate a Bionate 80A ring-shaped nucleus replacement. Methods : The ANSYS lumbar spine model made from lumbar spine X-rays and magnetic resonance images obtained from cadaveric spine specimens were used. All materials were assumed homogeneous, isotropic, and linearly elastic. We studied three options: intact spine, nucleotomy, and nucleus implant. Two loading conditions were evaluated at L 3 -L 4 , L 4 -L 5 , and L 5 -S 1 discs: a 1000 N axial compression load and this load after the addition of 8 Nm flexion moment in the sagittal plane plus 8 Nm axial rotation torque. Results : Maximum nucleus implant axial compression stresses in the range of 16–34 MPa and tensile stress in the range of 5–16 MPa, below Bionate 80A resistance were obtained. Therefore, there is little risk of permanent implant deformation or severe damage under normal loading conditions. Nucleotomy increased segment mobility, zygapophyseal joint and end plate pressures, and annulus stresses and strains. All these parameters were restored satisfactorily by nucleus replacement but never reached the intact status. In addition, annulus stresses and strains were lower with the nucleus implant than in the intact spine under axial compression and higher under complex loading conditions. Conclusions : Under normal loading conditions, there is a negligible risk of nucleus replacement, permanent deformation or severe damage. Nucleotomy increased segmental mobility, zygapophyseal joint pressures, and annulus stresses and strains. Nucleus replacement restored segmental mobility and zygapophyseal joint pressures close to the intact spine. End plate pressures were similar for the intact and nucleus implant conditions under both loading modes. Manufacturing customized nucleus implants is considered feasible, as satisfactory biomechanical performance is confirmed.

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Section: Methodsmentioning

confidence: 99%

“… 13 It has limitations as a computer simulation study but it is easy to use and mimics different clinical scenarios. 14 …”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Finite Element Analysis of a Bionate Ring-Shaped Customized Lumbar Disc Nucleus Prosthesis

Vanaclocha

Atienza

et al. 2021

ACS Appl. Bio Mater.

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“…) characterizes the edge direction(Li, Sang & Gao 2016;Luo et al 2016;R. & Chandra 2016;Uddin et al 2017;Punarselvam & Suresh 2019;Ranjbarzadeh, Saadi & Amirabadi 2020). An example of applying the non-linear edge detector to the CT images is illustrated in Fig.4.…”

mentioning

confidence: 99%

TPCNN: Two-path convolutional neural network for tumor and liver segmentation in CT images using a novel encoding approach

Aghamohammadi

Ranjbarzadeh

Naiemi

et al. 2021

Expert Systems with Applications

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Automatic liver and tumour segmentation in CT images are crucial in numerous clinical applications, such as postoperative assessment, surgical planning, and pathological diagnosis of hepatic diseases. However, there are still a considerable number of difficulties to overcome due to the fuzzy boundary, irregular shapes, and complex tissues of the liver. In this paper, for liver and tumor segmentation and to overcome the mentioned challenges a simple but powerful strategy is presented based on a cascade convolutional neural network. At the first, the input image is normalized using the Z-Score algorithm. This normalized image provides more information about the boundary of tumor and liver. Also, the Local Direction of Gradient (LDOG) which is a novel encoding algorithm is proposed to demonstrate some key features inside the image. The proposed encoding image is highly effective in recognizing the border of liver, even in the regions close to the touching organs. Then, a cascade CNN structure for extracting both local and semi-global features is used which utilized the original image and two other obtained images as the input data.Rather than using a complex deep CNN model with a lot of hyperparameters, we employ a simple but effective model to decrease the train and testing time. Our technique outperforms the state-ofthe-art works in terms of segmentation accuracy and efficiency.

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A comprehensive review of image denoising in deep learning

Jebur,

Zabil,

Hammood

et al. 2023

Multimed Tools Appl

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Non-Linear Filtering Technique Used for Testing the Human Lumbar Spine FEA Model

Cited by 7 publications

References 32 publications

Finite Element Analysis of a Bionate Ring-Shaped Customized Lumbar Disc Nucleus Prosthesis

Finite Element Analysis of a Bionate Ring-Shaped Customized Lumbar Disc Nucleus Prosthesis

TPCNN: Two-path convolutional neural network for tumor and liver segmentation in CT images using a novel encoding approach

A comprehensive review of image denoising in deep learning

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