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Purpose Vessel lumen centerline extraction is important for intraoperative tracking of abdominal vessels and guidance of endovascular instruments. Three-dimensional ultrasound has gained increasing acceptance as a safe and conveni...
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Purpose Vessel lumen centerline extraction is important for intraoperative tracking of abdominal vessels and guidance of endovascular instruments. Three-dimensional ultrasound has gained increasing acceptance as a safe and convenient surgical image guidance modality. We aimed to optimize vascular centerline detection and tracking in 3D ultrasound. Method To overcome the intrinsic limitation of low ultrasound image quality, an active contour method (snake) was used to track changes in vessel geometry. We tested two variants of a classic snake using the image gradient and gradient vector field (GVF) as external forces. We validated these methods in liver ultrasound images of 10 healthy volunteers, acquired at three breath-holding instances during the exhalation phase. We calculated the distances between the vessel centerlines as detected by algorithms and a gold standard consisting of manual annotations performed by an expert. Results Both methods (GVF and image gradient) can accurately estimate the actual centerlines with average Euclidean distances of 0.77 and 1.24 mm for GVF and gradient, respectively. Both methods can automatically follow vessel morphology and position changes. Conclusions The proposed approach is feasible for liver vessel centerline extraction from 3D ultrasound images. The algorithm can follow the movement of the vessels during respiration; further improvements of hardware components are needed for a real-time implementation.
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A method is proposed for generation of the centerline of 3D tubular shapes using an extensible-skeleton model. Starting from a user-selected point, the skeleton grown by iteratively adding subsequent centerline points within a pre...
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A method is proposed for generation of the centerline of 3D tubular shapes using an extensible-skeleton model. Starting from a user-selected point, the skeleton grown by iteratively adding subsequent centerline points within a prediction-estimation scheme controlled by a multi-scale analysis of the image moments. The location of the next point is predicted according the local orientation of the tubular structure. The coordinates of the predicted point are corrected under the influence of image forces and of prior model shape constraints. The extraction of artery centerlines from magnetic resonance angiography (MRA) images is described. The goal is a quantitative assessment of arterial stenoses based on cross-sectional diameters and areas of the vessel contours in the planes locally perpendicular to the centerline. For this purpose, iso-contours extraction based on an adaptive local iso-value have been implemented. The robustness and accuracy of the method have been demonstrated on MRA data on 5 reference phantoms and on 17 patients' carotid arteries, 97% of the centerlines were exploitable in the carotid arteries (100% in the phantoms). On average, the centerlines were extracted within 1 second, and the whole quantification process took less than 1 minute per artery, including interaction and display. The Mean difference (± standard deviation) between stenosis percentages, semi-automatically measured and visually estimated by radiologists, was 0.23% ± 7.89%. The reproducibility of the semi-automatic method was significantly better.
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Soft manipulator is a strong nonlinear system with high uncertainty. Real-time 3D shape estimation is the base for the control and application of soft manipulators. However, it is challenging to realize 3D shape estimation through...
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Soft manipulator is a strong nonlinear system with high uncertainty. Real-time 3D shape estimation is the base for the control and application of soft manipulators. However, it is challenging to realize 3D shape estimation through accurate modeling as the rigid manipulator. To deal with this issue, a real-time 3D centerline estimation framework based on stereo vision is proposed for the multi-section soft manipulator in this work. The contour of the manipulator is segmented accurately from the real-time images captured by the ZED camera using the machine vision method. The contour data is then clustered based on the self-organizing mapping (SOM) algorithm to form a 2D centerline. The linear overdetermined equation established by the camera projection model is figured out to obtain the optimal solution in the sense of least squares, and the 3D reconstruction is completed. In the simulation of the SOM algorithm, the parameters selection, simulation verification, and the comparison of various centerline extraction algorithms are completed. The results show that the SOM algorithm has more advantages to solve this work. Real-time bending experiments are carried out to verify the feasibility and robustness of the proposed framework, and performance evaluation experiments are also performed for accuracy and real-time performance. Compared with other research work, the framework in this work has high accuracy and real-time tracking performance.
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Multiple laser stripe measurement (MLSM) is a vital technique in optical three-dimensional (3D) measurement. The accurate extraction of the laser stripe centerlines plays a decisive role in achieving high measurement accuracy. How...
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Multiple laser stripe measurement (MLSM) is a vital technique in optical three-dimensional (3D) measurement. The accurate extraction of the laser stripe centerlines plays a decisive role in achieving high measurement accuracy. However, complex 3D measurement scenarios pose challenges due to various interferences, such as optical interference caused by dense stripes and no-ideal distribution caused by non-uniform reflectivity. To address these challenges, we propose an adaptive step size gradient centerline extraction method based on an 2D linear filter. This method incorporates local adaptive variable parameters for fine-tuning while utilizing global parameters. We validate its performance by conducting comprehensive comparative experiments with two commonly used methods. The results demonstrate that our proposed method enables more precise centerline extraction, exhibits enhanced stability, and yields lower measurement errors in complex 3D measurement conditions and highlight the effectiveness and superior performance of our method.
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We propose an algorithm for generating 18-connected skeletons and centerlines of 3D binary volume data sets. With of an ap- proximate minimum distance field, we ex- press skeletons as a set of clusters with a set of local maximum ...
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We propose an algorithm for generating 18-connected skeletons and centerlines of 3D binary volume data sets. With of an ap- proximate minimum distance field, we ex- press skeletons as a set of clusters with a set of local maximum paths(LMpaths). Each cluster consists of geometrically adja- Cent voxels with the same local maximum Value. Distinct clusters are connected by All possible LMpaths formed by local max- Imum voxels snaking along, at most, three Fixed directions until they meet other clus- Ters. As a 3D extension, we discuss an LMpath traveling on a straight line before And after reaching a saddle point.
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Abstract Purpose Most cardiology procedures are guided using X-ray (XR) fluoroscopy. However, the projective nature of the XR fluoroscopy does not allow for true depth perception as required for safe and efficient intervention gui...
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Abstract Purpose Most cardiology procedures are guided using X-ray (XR) fluoroscopy. However, the projective nature of the XR fluoroscopy does not allow for true depth perception as required for safe and efficient intervention guidance in structural heart diseases. For improving guidance, different methods have been proposed often being radiation-intensive, time-consuming, or expensive. We propose a simple 3D localization method based on a single monoplane XR projection using a co-registered centerline model.Methods The method is based on 3D anatomic surface models and corresponding centerlines generated from preprocedural imaging. After initial co-registration, 2D working points identified in monoplane XR projections are localized in 3D by minimizing the angle between the projection lines of the centerline points and the working points. The accuracy and reliability of the located 3D positions were assessed in 3D using phantom data and in patient data projected to 2D obtained during placement of embolic protection system in interventional procedures.Results With the proposed methods, 2D working points identified in monoplane XR could be successfully located in the 3D phantom and in the patient-specific 3D anatomy. Accuracy in the phantom (3D) resulted in 1.6?mm (±?0.8?mm) on average, and 2.7?mm (±?1.3?mm) on average in the patient data (2D).Conclusion The use of co-registered centerline models allows reliable and accurate 3D localization of devices from a single monoplane XR projection during placement of the embolic protection system in TAVR. The extension to different vascular interventions and combination with automatic methods for device detection and registration might be promising.
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In urban areas, there is a necessity to evaluate the performance of existing structures during and after the construction of nearby tunnels. Therefore, a 3D numerical modeling technique is needed to consider the geometrical intera...
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In urban areas, there is a necessity to evaluate the performance of existing structures during and after the construction of nearby tunnels. Therefore, a 3D numerical modeling technique is needed to consider the geometrical interactions between the tunnel and the existing structures. To validate the results of 3D numerical simulation for the tunneling process, the surface settlement trough resulted from the numerical model has been compared with field measurements of a selected case study (Second Heinenoord Tunnel in Netherlands). The 3D finite element model has also been used to evaluate the raft settlements and bending moments. The study is performed during and after the tunnel advancement process. In addition, the effect of related parameters, such as soil relative density (D-r), tunnel diameter (D), tunnel cover (Z), horizontal clearance between the raft centerline and the tunnel centerline (CL), raft inclination angle (i), and raft thickness (d), have been studied.
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Detection of blocks in coronary arteries is becoming crucial interest for early detection of heart attacks. In this paper we propose a framework for detection of plaque in coronary arteries from cardio vascular magnetic resonance ...
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Detection of blocks in coronary arteries is becoming crucial interest for early detection of heart attacks. In this paper we propose a framework for detection of plaque in coronary arteries from cardio vascular magnetic resonance imaging(CMRI). It is a quantitative tool for the assessment of cardiovascular diseases. First, select a region of interest and segment the region of coronary artery using enhanced region based active contour (ERAC). Secondly the centreline extraction and lumen segmentation are integrated to extract the artery centreline using geometric moments and the vessel direction using Hessian matrix and segment the vessel lumen in each slice using ERAC. A boundary searching method is adapted to fine tune the segmented surface in each slice of CMRI image. Third, the soft plaques in the coronary artery are extracted by thresholding the segmented region. Finally a 3D visualization of blood flow in coronary artery is presented and the volume of blood flow is calculated. In the experiments we have employed 22 datasets of CMRI images. The experimental results show an average accuracy of 97.6% and with a mean and standard deviation of false discovery rate of 2.48 +/- 0.002.
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Background: Flow dynamics are a significant factor in the development and possible rupture of the aneurysms. Therefore, it is close to reason to present detailed data on the realistic 3D surface and internal geometry of a primary ...
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Background: Flow dynamics are a significant factor in the development and possible rupture of the aneurysms. Therefore, it is close to reason to present detailed data on the realistic 3D surface and internal geometry of a primary aortoenteric fistula, i.e. of its fistulous tract.
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An ideal TF coil shape or centerline should be such that the TF coil is subjected to constant tension. The Princeton-D and the Modified-D are widely used as constant-tension centerlines for designing TF coil, however, our analyses...
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An ideal TF coil shape or centerline should be such that the TF coil is subjected to constant tension. The Princeton-D and the Modified-D are widely used as constant-tension centerlines for designing TF coil, however, our analyses show that their tensions are not fully constant. The reason is that the magnetic field used to calculate the centerlines is inaccurate. In this work, we propose an approach of calculating the Optimized-D shape with improved tension constancy. First, the Princeton-D and the Modified-D are introduced and their tension nonconstancies are revealed. Then, a code is written to calculate the accurate toroidal fields. Next, the Optimized-D coil shape is obtained through a semi-analytical iteration process. Finally, for the three D shapes, the relationship between the TF coil parameters are discussed. Our results indicate that the Optimized-D shape realizes a noteworthy improvement in tension constancy.
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