In recent years, volumetric (3D) cardiac ultrasound imaging has become more readily available in daily clinical practice due to the introduction of matrix array transducer technology. To date, quantitative analysis of...
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ISBN:
(纸本)9781424443895;9781424443901
In recent years, volumetric (3D) cardiac ultrasound imaging has become more readily available in daily clinical practice due to the introduction of matrix array transducer technology. To date, quantitative analysis of these data sets typically requires a significant amount of user interaction. Recently, our teams introduced methods that could help in automating this process. On the one hand, an edge detectionalgorithm in combination with a deformable subdivision surface was presented for automatic segmentation of the LV cavity. A real-time, dynamic implementation of this segmentation approach in combination with a Kalman filter allows tracking the subendocardial boundary throughout the cardiac cycle. This method is referred to as RCTL. On the other hand, an automatic 3D motion estimation algorithm was presented in which subsequent image volumes are elastically registered using a B-spline transformation field. This method is called splineMIRIT. Both methods were applied to clinical data to extract relevant functional parameters on global left ventricular (LV) function (i.e. stroke volume (SV) and ejection fraction (EF)). Both methods show a good correlation with the reference method and might thus be used for fully automated estimation of global LV function. Given that RCTL is a fully integrated method (accounting for both segmentation and tracking) it seems to be the better approach towards extracting these parameters. However, whether this remains true when assessing parameters for regional LV function remains to be investigated.
Many researchers are looking to take their work from a simulation environment and implement it on an embedded DSP platform. This is primarily driven by the need to demonstrate that the research is viable commercially....
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ISBN:
(纸本)9781617388767
Many researchers are looking to take their work from a simulation environment and implement it on an embedded DSP platform. This is primarily driven by the need to demonstrate that the research is viable commercially. This paper will provide an overview of the different types of hardware and software development platforms that are available. It will then provide a summary of the software design techniques that are required to maximise the efficiency of code on current embedded DSP platforms. These will be demonstrated using an implementation of a Canny Edge detectionalgorithm on a DM6437 Evaluation Module.
Combined with the theories of intermolecular multiple-quantum coherences (iMQCs) and distant dipolar field (DDF) effect, edge detection effect due to chemical shift variation in magnetic resonance imaging (MRI) was si...
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ISBN:
(纸本)9781424425105
Combined with the theories of intermolecular multiple-quantum coherences (iMQCs) and distant dipolar field (DDF) effect, edge detection effect due to chemical shift variation in magnetic resonance imaging (MRI) was simulated and discussed deeply using an efficient numerical algorithm based on the nonlinear Bloch equations. Simulation results show that, different from the conventional MRI signal, chemical shift in iMQC MRI can provide new imaging information, an edge detection method to search regions containing spins with chemical shift offset. The edge detection method can present plentiful information about various kinds of edges of object regions.
In this paper we analyze the robustness of watermarking method in still images using Haar, Daubecheies and Biorthogonal wavelets. The embedding process uses a canny edge detection method and hides the watermark with t...
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ISBN:
(纸本)9781424433964
In this paper we analyze the robustness of watermarking method in still images using Haar, Daubecheies and Biorthogonal wavelets. The embedding process uses a canny edge detection method and hides the watermark with the perceptual considerations on different modalities of images. The extraction scheme uses non-blind method to retrieve the watermark. We simulate the JPEG Compression attack with different quality standards to check the robustness and prove the authenticity of the digital content.
Edge detection is a crucial and basic tool in image segmentation. The key of edge detection in gray image is to detect more edge details, reduce the noise impact to the largest degree, and threshold the edge image aut...
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ISBN:
(纸本)9783540743767
Edge detection is a crucial and basic tool in image segmentation. The key of edge detection in gray image is to detect more edge details, reduce the noise impact to the largest degree, and threshold the edge image automatically. According to this, a novel edge detection method based on mathematic morphology and iterative thresholding is proposed in this paper. A modified morphological transform through regrouping the priorities of several morphological transforms based on contour structuring elements is realized first, and then an edge detector is defined by using the multi-scale operation of the modified morphological transform to detect the gray-scale edge map. Finally, a new iterative thresholding algorithm is applied to obtain the binary edge image. Comparative study with other morphological methods reveals its Superiority over de-noising capacity, edge details protection and un-sensitivity to the shape of the structuring elements.
In this paper, a fast multi-scale edge detection approach is proposed based on the theories of image diffusion and curve evolution. In comparison with the previous edge detection approaches, edge detection is performe...
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ISBN:
(纸本)9780769530635
In this paper, a fast multi-scale edge detection approach is proposed based on the theories of image diffusion and curve evolution. In comparison with the previous edge detection approaches, edge detection is performed in two steps: beginning by detecting the initial contours at a courser scale that is performed by using a linear diffusion coupling with the denoising effect and gray transformation, then the obtained contour curves are mapped and further refined up to finer scales using the fast Hermes algorithm. By this way, (he experimental results show that the proposed edge detection approach are more promising than the existing methods for object detection on general images, especially on medical images.
Edge detection based on multiscale wavelet transform is one of the important algorithms in images edge detection. In large scale it is strongly anti-noise, and in small scale it can accurately locate edge. In order to...
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ISBN:
(纸本)9781424406043
Edge detection based on multiscale wavelet transform is one of the important algorithms in images edge detection. In large scale it is strongly anti-noise, and in small scale it can accurately locate edge. In order to exploit both advantages, a new single threshold edge detection method based on edgefusion is developed using finite element Method (FEM) multiscale wavelet transform. Firstly, edge effective envelope is developed, in the range of effective edge envelop, using FEM track algorithms for edge fusion and detection to local edge point according to FEM cell topology. Secondly, A single threshold is used for accurate locate edge of detection. The validly of the algorithm is proved by experiments on both synthetic and natural image.
The first step for video-content analysis, content-based video browsing and retrieval is the partitioning of a video sequence into shots. A shot is the fundamental unit of a video, it captures a continuous action from...
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The first step for video-content analysis, content-based video browsing and retrieval is the partitioning of a video sequence into shots. A shot is the fundamental unit of a video, it captures a continuous action from a single camera and represents a spatio-temporally coherent sequence of frames. Thus, shots are considered as the primitives for higher level content analysis, indexing and classification. Although many video shot boundary detection algorithms have been proposed in the literature, in most approaches, several parameters and thresholds have to be set in order to achieve good results. In this paper, we present a robust learning detector of sharp cuts without any threshold to set nor any pre-processing step to compensate motion or post-processing filtering to eliminate false detected transitions. The experiments, following strictly the TRECVID 2002 competition protocol, provide very good results dealing with a large amount of features thanks to our kernel-based SVM classifier method.
The problem of edge detection in noisy images is addressed in this paper. It is shown that the performance of an existing edge detection method, known as the stochastic gradient operator, can be significantly improved...
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ISBN:
(纸本)0780331222
The problem of edge detection in noisy images is addressed in this paper. It is shown that the performance of an existing edge detection method, known as the stochastic gradient operator, can be significantly improved by incorporating three new features: (i) a robust technique for estimating the noise variance and autocorrelation function of the signal, (ii) a block-by-block adaptation of the gradient mask, and (iii) calculation of a threshold based on Rayleigh distribution. The performance of the proposed technique is compared with that of some existing ones.
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