Accuracy Evaluation of 3D Reconstruction of Transfemoral Residual Limb Model Using Basic Spline Interpolation

Jamaludin, Mohd Syahmi; Hanafusa, Akihiko

doi:10.1007/978-981-10-9038-7_125

Cited by 5 publications

(6 citation statements)

References 5 publications

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“…When inputting the whole slice tumor image into the U-net based deep learning model, the boundaries of the lesions were automatically determined without any pre-or postprocessing (Supplementary A0). The whole tumor volume was then reconstructed on multiple 2-dimensional (2D) image slices by interpolation [26]. During the reconstruction of the whole volume lesions, wavelet bandpass filtering, isotropic resampling, and grayscale discretization were performed to obtain heterogeneity parameters of different characteristics, and thus improve the robustness and reproducibility of the extracted heterogeneity parameters [27][28][29].…”

Section: Nodule Segmentation and Radiomics Feature Extractionmentioning

confidence: 99%

A CT-based radiomics nomogram for prediction of lung adenocarcinomas and granulomatous lesions in patient with solitary sub-centimeter solid nodules

et al. 2020

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Purpose: To develop a radiomics nomogram based on computed tomography (CT) images that can help differentiate lung adenocarcinomas and granulomatous lesions appearing as sub-centimeter solid nodules (SCSNs). Materials and methods: The records of 214 consecutive patients with SCSNs that were surgically resected and histologically confirmed as lung adenocarcinomas (n = 112) and granulomatous lesions (n = 102) from 2 medical institutions between October 2011 and June 2019 were retrospectively analyzed. Patients from center 1 ware enrolled as training cohort (n = 150) and patients from center 2 were included as external validation cohort (n = 64), respectively. Radiomics features were extracted from non-contrast chest CT images preoperatively. The least absolute shrinkage and selection operator (LASSO) regression model was used for radiomics feature extraction and radiomics signature construction. Clinical characteristics, subjective CT findings, and radiomics signature were used to develop a predictive radiomics nomogram. The performance was examined by assessment of the area under the receiver operating characteristic curve (AUC). Results: Lung adenocarcinoma was significantly associated with an irregular margin and lobulated shape in the training set (p = 0.001, < 0.001) and external validation set (p = 0.016, = 0.018), respectively. The radiomics signature consisting of 22 features was significantly associated with lung adenocarcinomas of SCSNs (p < 0.001). The radiomics nomogram incorporated the radiomics signature, gender and lobulated shape. The AUCs of combined model in the training and external validation dataset were 0.885 (95% confidence interval [CI]: 0.823-0.931), 0.808 (95% CI: 0.690-0.896), respectively. Decision curve analysis (DCA) demonstrated that the radiomics nomogram was clinically useful.

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Section: Nodule Segmentation and Radiomics Feature Extractionmentioning

confidence: 99%

A CT-based radiomics nomogram for prediction of lung adenocarcinomas and granulomatous lesions in patient with solitary sub-centimeter solid nodules

et al. 2020

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“…Thus, an adjustment can be made to the socket design before it has been fabricated. Although the calibration of a 3D model has been previously conducted [24], the details, particularly the scar from the post-treatment at the distal end, were not highlighted. In a future study, increasing the number of subjects will be our top priority to enhance the statistical analysis and consider subject-specific material properties through advanced finite element (FE) model creation.…”

Section: Discussionmentioning

confidence: 99%

Analysis of Pressure Distribution in Transfemoral Prosthetic Socket for Prefabrication Evaluation via the Finite Element Method

et al. 2019

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In this study, we estimated and validated the pressure distribution profile between the residuum and two types of prosthetic sockets for transfemoral amputees by utilizing a finite element analysis. Correct shaping of the socket for an appropriate load distribution is a critical process in the design of lower-limb prosthesis sockets. The pressure distribution profile provides an understanding of the relationship between the socket design and the level of subject comfortability. Estimating the pressure profile is important, as it helps improve the prosthesis through an evaluation of the socket design before it undergoes the fabrication process. This study focused on utilizing a magnetic resonance imaging (MRI)-based three-dimensional (3D) model inside a predetermined finite element simulation. The simulation was predetermined by mimicking the actual socket-fitting environment. The results showed that the potential MRI-based 3D model simulation could be used as an estimation tool for a pressure distribution profile due to the high correlation coefficient value (R 2 > 0.8) calculated when the pressure profiles were compared to the experiment data. The simulation also showed that the pressure distribution in the proximal area was higher (~30%) than in the distal area of the prosthetic socket for every subject. The results of this study will be of tremendous interest for fabricators through the use of a finite element model as an alternative method for the prefabrication and evaluation of prosthetic sockets. In future prosthetic socket fabrications, less intervention will be required in the development of a socket, and the participation of the subject in the socket-fitting session will not be necessary. The results suggest that this study will contribute to expanding the development of an overall prefabrication evaluation system to allow healthcare providers and engineers to simulate the fit and comfort of transfemoral prosthetics.

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Section: Finite Element Model Constructionmentioning

confidence: 99%

“…The socket model was created using the real size of the prosthetic and not a residuum shape offset as practiced in most previous research studies. The design method has been discussed in detail in Reference [14]. Creo 3 (PTC Ltd., New Delhi, India) is a CAD software used to generate a surface dimension file format such as an initial graphics exchange specification (IGES) file and standard triangular language (STL) file and it enabled the meshing process to be conducted directly without file conversion.…”

Section: Finite Element Model Constructionmentioning

confidence: 99%

Development of an Evaluation System for Magnetic Resonance Imaging Based Three-Dimensional Modeling of a Transfemoral Prosthetic Socket Using Finite Elements

et al. 2019

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Recent technologies have suggested the utilization of three-dimensional (3D) printing technology to enhance the fabrication accuracy of prosthetics. Accordingly, simulations are used to obtain precise parameters for subject-specified prosthetic socket. This study proposes an evaluation system to measure the accuracy of a subject-specific 3D transfemoral residuum model during the interaction with the socket in conjunction with the application of finite element methods. The proposed system can be used in future validations of socket fabrication. The evaluation is based on the measurement of the residuum’s soft tissue deformation inside two types of prosthetic sockets. In comparison with other studies, the 3D models were constructed with magnetic resonance images (MRI) with the aid of computer-aided design (CAD) software. The measurement of soft tissue deformation was conducted based on the measurement of the volumetric value of fat, muscle and skin in the pre- and post-donning phases. The result yielded a promising correlation coefficient value between the simulation and the experiment in the soft tissue deformation evaluation. The relation of the muscle–fat ratio in the residuum is extremely important in the determination of the ability of the prosthetic to deform. The environment during the socket fitting session was similar to that defined by the set boundary conditions in simulations. In view of the promising results of this study, the evaluation system proposed herein is considered reliable and is envisaged to be used in future research.

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Accuracy Evaluation of 3D Reconstruction of Transfemoral Residual Limb Model Using Basic Spline Interpolation

Cited by 5 publications

References 5 publications

A CT-based radiomics nomogram for prediction of lung adenocarcinomas and granulomatous lesions in patient with solitary sub-centimeter solid nodules

A CT-based radiomics nomogram for prediction of lung adenocarcinomas and granulomatous lesions in patient with solitary sub-centimeter solid nodules

Analysis of Pressure Distribution in Transfemoral Prosthetic Socket for Prefabrication Evaluation via the Finite Element Method

Development of an Evaluation System for Magnetic Resonance Imaging Based Three-Dimensional Modeling of a Transfemoral Prosthetic Socket Using Finite Elements

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