In this paper, we present a new reconstruction method with volumetric registration and semi-automatic segmentation in a multi-view 3D freehand ultrasound imaging system. The new volumetric registration approach is per...
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ISBN:
(纸本)1424407850
In this paper, we present a new reconstruction method with volumetric registration and semi-automatic segmentation in a multi-view 3D freehand ultrasound imaging system. The new volumetric registration approach is performed on binarized walls using non-linear least squares. It can provide accurate multi-view reconstructions despite significant rigid target motion between different acoustic window acquisitions. A hybrid adaptive gradient vector flow (GVF) geometric active contour (GAC) model is used for image sequence segmentation. It allows for relatively simple initialization of the deformable model, while avoiding edge leaking at poor edges and small boundary gaps. The algorithms were validated on four ultrasound phantom data sets (eight sequences of a total of 336 images) and two echocardiography data sets (four sequences for a total of 75 images). Quantitative evaluation shows that automatic segmentation is comparable with manual segmentation. Using breath-holding and cardiac gating, volume estimates from multiview reconstructions of the left-ventricle were found to be in better agreement with clinical estimates than volumes estimated from single view reconstructions.
We propose a new semi-automatic segmentation strategy on echocardiographic images, which combines a recently introduced gradient vector flow (GVF) fast geometric active contour (GAC) model and a modified level sets me...
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ISBN:
(纸本)1424400694
We propose a new semi-automatic segmentation strategy on echocardiographic images, which combines a recently introduced gradient vector flow (GVF) fast geometric active contour (GAC) model and a modified level sets methods applied to echocardiographic data by Corsi et al.. We call it adaptive GVF GAC model. We note that echocardiographic images are characterized by high levels of speckle noise, weakly-defined boundaries and severe gaps. We show that the new method, adapted for single object segmentation, can provide significantly improved performance over a competing level set method, and that was in turn shown to perform better than the original gradient vector flow method. The new method modifies the advection term in the speed function adoptively by estimating how close the propagated curve is to the target boundaries. We show both synthetic and real, freehand ultrasound image and echocardiographic image examples to illustrate the robustness and accuracy of the new segmentation method
In this paper, we present a real-time amplitude-modulation frequency-modulation (AM-FM) analysis system, and apply the system to M-mode ultrasound video. The estimated frequency-modulation (FM) process is shown to cap...
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In this paper, we present a real-time amplitude-modulation frequency-modulation (AM-FM) analysis system, and apply the system to M-mode ultrasound video. The estimated frequency-modulation (FM) process is shown to capture the cardiac wall deformation, while the amplitude modulation process is shown to follow changes in cardiac wall material. Results from segmenting the septum and left-ventricle walls are also presented.
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