Segmentation-based regularization of dynamic SPECT reconstructions

Abstract-Dynamic SPECT reconstruction using a single slow camera rotation is a highly underdetermined problem, which requires the use of regularization techniques to obtain useful results. The dSPECT algorithm We test this approach with a digital phantom simulating the kinetics of Tc99m-DTPA in the renal system, including healthy and unhealthy behaviour. Summed TACs for each kidney and the bladder were calculated for the spatially regularized and nonregularized reconstructions, and compared to the true values. The TACs for the two kidneys were noticeably improved in every case, while TACs for the smaller bladder region were unchanged. Furthermore, in two cases where the segmentation was intentionally done incorrectly, the spatially regularized reconstructions were still as good as the non-regularized ones. In general, the segmentation-based regularization improves TAC quality within ROIs, as well as image contrast

Semi-automatic algorithm for construction of the left ventricular area variation curve over a complete cardiac cycle

<p>Abstract</p> <p>Background</p> <p>Two-dimensional echocardiography (2D-echo) allows the evaluation of cardiac structures and their movements. A wide range of clinical diagnoses are based on the performance of the left ventricle. The evaluation of myocardial function is typically performed by manual segmentation of the ventricular cavity in a series of dynamic images. This process is laborious and operator dependent. The automatic segmentation of the left ventricle in 4-chamber long-axis images during diastole is troublesome, because of the opening of the mitral valve.</p> <p>Methods</p> <p>This work presents a method for segmentation of the left ventricle in dynamic 2D-echo 4-chamber long-axis images over the complete cardiac cycle. The proposed algorithm is based on classic image processing techniques, including time-averaging and wavelet-based denoising, edge enhancement filtering, morphological operations, homotopy modification, and watershed segmentation. The proposed method is semi-automatic, requiring a single user intervention for identification of the position of the mitral valve in the first temporal frame of the video sequence. Image segmentation is performed on a set of dynamic 2D-echo images collected from an examination covering two consecutive cardiac cycles.</p> <p>Results</p> <p>The proposed method is demonstrated and evaluated on twelve healthy volunteers. The results are quantitatively evaluated using four different metrics, in a comparison with contours manually segmented by a specialist, and with four alternative methods from the literature. The method's intra- and inter-operator variabilities are also evaluated.</p> <p>Conclusions</p> <p>The proposed method allows the automatic construction of the area variation curve of the left ventricle corresponding to a complete cardiac cycle. This may potentially be used for the identification of several clinical parameters, including the area variation fraction. This parameter could potentially be used for evaluating the global systolic function of the left ventricle.</p

Sectoral Transformations in Neo-Patrimonial Rentier States: Tourism Development and State Policy in Egypt

This article challenges claims that liberalising state regulated markets in developing countries may induce lasting economic development. The analysis of the rise of tourism in Egypt during the last three decades suggests that the effects of liberalisation and structural adjustment are constrained by the neo-patrimonial character of the Egyptian political system. Since the decline of oil rent revenues during the 1980s tourism development was the optimal strategy to compensate for the resulting fiscal losses. Increasing tourism revenues have helped in coping with macroeconomic imbalances and in avoiding more costly adjustment of traditional economic sectors. Additionally, they provided the private elite with opportunities to generate large profits. Therefore, sectoral transformations due to economic liberalisation in neo-patrimonial Rentier states should be described as a process, which has led to the diversification of external rent revenues, rather than to a general downsizing of the Rentier character of the economy

EXACT INTEGRATION OF DIFFUSION ORIENTATION DISTRIBUTION FUNCTIONS FOR GRAPH-BASED DIFFUSION MRI ANALYSIS

Graph-based image analysis methods are increasingly being applied to diffusion MRI (dMRI) analysis. Unfortunately, weighting the graph for these methods involves solving a complex integral of an orientation distribution function (ODF). To date, these integrals have been approximated numerically at high computational cost and have resulted in numerical approximation errors that degrade dMRI analysis results. By exploiting a spherical harmonic representation of the ODF, we derive for the first time an analytical solution to the edge weight integrals used in graph-based dMRI analysis. We further show that the computational efficiency of our analytical integration is over forty times faster than numerical approximation schemes on typical data sets. Further, we incorporate our exact integration scheme into an existing graph-based probabilistic tractography method and show a reduction in error accumulation in the resulting tractograms. Index Terms — Diffusion MRI, graph-based analysis, tractography, numerical analysis, spherical harmonic

Consistent Information Content Estimation for Diffusion Tensor MR Images

Abstract—We propose novel information content estimators for diffusion tensor images using binless approaches based on nearest-neighbour distances. Combining these estimators with existing tensor distance metrics allows us to generate entropy estimates that are consistent and accurate for diffusion tensor data. Further, we are able to obtain such estimators without having to reduce the dimensionality of the tensor data to the point where a binning estimator can be reliably used. We test our estimators in the context of noise estimation, image segmentation, and image registration. Results on 12 datasets from LBAM and 50 datasets from LONI show our estimators more accurately reflect the underlying DTI data and provide faster convergence rates for image segmentation and registration algorithms. Keywords-diffusion tensor imaging; entropy; mutual information; noise estimation; image segmentation; image registration I