The overall scheme aimed at three-dimensional reconstruction of vascular networks from two X-ray projections relies on the efficient detection of vessels in the image frames. The authors describe an intermediate proce...
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The overall scheme aimed at three-dimensional reconstruction of vascular networks from two X-ray projections relies on the efficient detection of vessels in the image frames. The authors describe an intermediate processing level to control the information issued by low-level procedures. Its role consists of filtering and combining centerlines and contours in such a way that only the relevant vessels are preserved.< >
The authors develop an empirical measure for the selection of the Gaussian filter that is commonly used for edge enhancement. The measure is based totally on the image at hand. Edge enhancement by a Gaussian filter ha...
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The authors develop an empirical measure for the selection of the Gaussian filter that is commonly used for edge enhancement. The measure is based totally on the image at hand. Edge enhancement by a Gaussian filter has two distinct advantages: (1) the filter is fully described by a single parameter, the standard deviation sigma ; (2) the two-dimensional filter is separable and can be easily implemented. The filter's spatial support is a function of sigma . This support is normally in the range of +or-3.5 sigma . An empirical measure is described for the selection of the Gaussian filter's spatial support using the power spectrum density of the input image. Classic Fourier analysis is used to obtain a measure for the spatial support of the Gaussian filter given a particular image. Experimental results suggest that this measure can be used as an aid in deciding the Gaussian filter's spatial support needed to enhance the edges.< >
The problem of reconstructing a transmission attenuation image is addressed. The estimation procedure is based on a Bayesian formulation incorporating a Poisson likelihood model that includes scatter for the transmiss...
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The problem of reconstructing a transmission attenuation image is addressed. The estimation procedure is based on a Bayesian formulation incorporating a Poisson likelihood model that includes scatter for the transmission data and a Markov random field prior. The results obtained using this approach result in improved accuracy in computing the ACFs (attenuation correction factors). A transmission image is also useful for reconstructing anatomical landmarks for use in cross-modality registration. A third advantage of reconstruction of the transmission image is that, if the patient moves between the transmission and one or more emission scans, the reconstructed transmission image can be used to generate ACFs for any new position. Several candidate optimization techniques are investigated, and the quantitative accuracy of the reconstructed images is evaluated.< >
Software calipers allowing the measurement of the distances between pairs of manually defined picture elements in digitized images may be useful tools for a rapid assessment of the morphology of coronary vessels, e.g....
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Software calipers allowing the measurement of the distances between pairs of manually defined picture elements in digitized images may be useful tools for a rapid assessment of the morphology of coronary vessels, e.g. for choosing the appropriate balloon or stent sizes before or during cardiac intervention procedures. In this paper we have studied extensively the advantages and limitations of two manual software calipers - one developed for a PC-based cinefilm analysis workstation, the other for the Philips DCI system. Based on analyses of a perspex vessel phantom with 17 sectors of known size filled with different concentrations (50 and 100%) of the contrast agent and acquired at two kV-levels (68 and 92 kV), it was found that the cinefilm approach is characterized by a very small overall (averaged over te data from three observers) systematic overestimation of 0.03 mm, and the DCI system by a systematic underestimation of 0.07 mm;the worst case accuracy value for an individual observer on frames with 100% contrast dye concentration was 0.20 mm for cinefilm, and -0.34 mm for the DCI, respectively. The overall variabilities in the measurements (precision) were almost identical for the two approaches (overall 0.07 and 0.08 mm for the cinefilm and digital approaches, respectively, and worst case for individual observers on the 100% contrast frames, 0.16 and 0.13 mm, respectively. Inverting the images (bright or dark contrast containing structures) of the phantom at 100% contrast concentration and acquired at 62 kV had no significant effect on the results obtained with the cinefilm analysis system (overall accuracy -0.12 mm for both situations), whereas it had on the results from the DCI system (overall accuracies -0.29 (dark vessels on bright background) and -0.08 mm (bright vessels on dark background), respectively). Enhancing the digital images on the DCI with unsharp masking techniques did not significantly influence the measurement accuracy and precision. Finally,
An algorithm for detecting neural processes in serial optical sections for use in an automated three-dimensional neural reconstruction system is presented. This parsimonious, nonlinear, psychophysically motivated algo...
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An algorithm for detecting neural processes in serial optical sections for use in an automated three-dimensional neural reconstruction system is presented. This parsimonious, nonlinear, psychophysically motivated algorithm addresses the problems specific to neural element detection and localization, viz., images with minimal resolution, operators with small spatial supports, highly curved, filamentous features, large variation in feature intensity profile, poor signal-to-noise ratio, and determination of depth without stereo. One first finds the magnitude and orientation of the maximum intensity second directional derivative. A family of curves is locally fitted to these data, and the projections of the data on the curve family are found. If a pixel lies on a curve with sufficient total projection, it is labeled with the magnitude, orientation, curvature, spatial extent, and element displacement. Depth is interpolated from the spatial extent data for corresponding neighborhoods in three adjacent (in depth) images by using an approximation to the depth-dependent optical point spread function. Experimental results using photomicrographs of cat visual cortex are presented.< >
Computing a curvature function on a digitized boundary is an ill-posed problem due to the discrete nature of the boundary. Thus, the boundary needs to be smoothed before computing the curvature function. The authors u...
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Computing a curvature function on a digitized boundary is an ill-posed problem due to the discrete nature of the boundary. Thus, the boundary needs to be smoothed before computing the curvature function. The authors use a constrained regularization technique to obtain the optimal smooth boundary. The curvature function is computed from this optimal smooth boundary. This method solves a common critical problem of current curvature estimation methods in determining a unique smoothing factor. This method is used to derive a curvature function which is invariant under rotation, scale, and translation.< >
The authors develop a path metric for sequential search based on the linear model. The metric forms the heart of an edge-linking algorithm that combines edge elements enhanced by an optimal filter. From a starting nod...
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The authors develop a path metric for sequential search based on the linear model. The metric forms the heart of an edge-linking algorithm that combines edge elements enhanced by an optimal filter. From a starting node, transitions are made to the goal nodes by a maximum likelihood metric. This metric requires only local calculations on the search space and its use in edge linking provides more accurate results than other linking techniques.< >
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