Three-dimensional reconstruction of stenosed coronary artery segments with assessment of the flow impedance

In this paper preliminary results of a study about the diagnostic benefits of 3D visualization and quantitation of stenosed coronary artery segments are presented. As is well known, even biplane angiographic images do not provide enough information for binary reconstruction. Therefore,a priori information about the slice to be reconstructed must be incorporated into the reconstruction algorithm. One approach is to assume a circular cross-section of the coronary artery. Hence, the diameter is estimated from the contours of the vessels in both projections. Another approach is to search for a solution of the reconstruction problem close to the previously reconstructed adjacent slice. In this paper we follow the first method based on contour information. The reconstructed coronary segment is visualized in three dimensions. Based on the obtained geometry of the obstruction the pertinent blood flow impedance is estimated on the basis of fluid dynamic principles. The results of applying the reconstruction algorithms to clinical coronary biplane exposures are presented with an indication of the assessed flow impedance

Level-Set Based Artery-Vein Separation in Blood Pool Agent CE-MR Angiograms

Blood pool agents (BPAs) for contrast-enhanced (CE) magnetic-resonance angiography (MRA) allow prolonged imaging times for higher contrast and resolution. Imaging is performed during the steady state when the contrast agent is distributed through the complete vascular system. However, simultaneous venous and arterial enhancement in this steady state hampers interpretation. In order to improve visualization of the arteries and veins from steady-state BPA data, a semiautomated method for artery-vein separation is presented. In this method, the central arterial axis and central venous axis are used as initializations for two surfaces that simultaneously evolve in order to capture the arterial and venous parts of the vasculature using the level-set framework. Since arteries and veins can be in close proximity of each other, leakage from the evolving arterial (venous) surface into the venous (arterial) part of the vasculature is inevitable. In these situations, voxels are labeled arterial or venous based on the arrival time of the respective surface. The evolution is steered by external forces related to feature images derived from the image data and by internal forces related to the geometry of the level sets. In this paper, the robustness and accuracy of three external forces (based on image intensity, image gradient, and vessel-enhancement filtering) and combinations of them are investigated and tested on seven patient datasets. To this end, results with the level-set-based segmentation are compared to the reference-standard manually obtained segmentations. Best results are achieved by applying a combination of intensity- and gradient-based forces and a smoothness constraint based on the curvature of the surface. By applying this combination to the seven datasets, it is shown that, with minimal user interaction, artery-vein separation for improved arterial and venous visualization in BPA CE-MRA can be achieved

Vessel Axis Tracking Using Topology Constrained Surface Evolution

An approach to three-dimensional vessel axis tracking based on surface evolution is presented. The main idea is to guide the evolution of the surface by analyzing its skeleton topology during evolution, and imposing shape constraints on the topology. For example, the intermediate topology can be processed such that it represents a single vessel segment, a bifurcation, or a more complex vascular topology. The evolving surface is then re-initialized with the newly found topology. Re-initialization is a crucial step since it creates probing behavior of the evolving front, encourages the segmentation process to extract the vascular structure of interest and reduces the risk on leaking of the curve into the background. The method was evaluated in two computed tomography angiography applications: (i) extracting the internal carotid arteries including the region in which they traverse through the skull base, which is challenging due to the proximity of bone structures and overlap in intensity values, and (ii) extracting the carotid bifurcations including many cases in which they are severely stenosed and contain calcifications. The vessel axis was found in 90% (18/20 internal carotids in ten patients) and 70% (14/20 carotid bifurcations in a different set of ten patients) of the cases

Діяльність волосних правлінь Чернігівщини в першій пол. ХІХ ст. по організації рекрутської повинності

У статті проаналізовано законодавство Російської імперії щодо комплектування армії в першій пол. ХІХ ст. та проведення військових реформ у Чернігівській губернії. Показано діяльність волосних правлінь Чернігівщини по організації рекрутської повинності державних селян та козаків.В статье проанализировано законодательство Российской империи относительно комплектации армии в первой пол. ХІХ в. и проведение военных реформ в Черниговской губернии. Показано деятельность волостных правлений Черниговщины по организации рекрутской повинности государственных крестьян и казаков.The legislation of the Russian Empire concerning the brining army up to strength in the first half of XIX century and the military reform in the Chernihiv province were analyzed in this article. The activity of the volost boards in the Chernihiv region connected with the organizing the recruit obligations of state peasants and Cossacks are shown in it

Vessel enhancing diffusion: a scale space representation of vessel

A method is proposed to enhance vascular structures within the framework of scale space theory. We combine a smooth vessel filter which is based on a geometrical analysis of the Hessian's eigensystem, with a non-linear anisotropic diffusion scheme. The amount and orientation of diffusion depend on the local vessel likeliness. Vessel enhancing diffusion (VED) is applied to patient and phantom data and compared to linear, regularized Perona-Malik, edge and coherence enhancing diffusion. The method performs better than most of the existing techniques in visualizing vessels with varying radii and in enhancing vessel appearance. A diameter study on phantom data shows that VED least affects the accuracy of diameter measurements. It is shown that using VED as a preprocessing step improves level set based segmentation of the cerebral vasculature, in particular segmentation of the smaller vessels of the vasculature

Automatic nuclei segmentation in H&E stained breast cancer histopathology images

The introduction of fast digital slide scanners that provide whole slide images has led to a revival of interest in image analysis applications in pathology. Segmentation of cells and nuclei is an important first step towards automatic analysis of digitized microscopy images. We therefore developed an automated nuclei segmentation method that works with hematoxylin and eosin (H&E) stained breast cancer histopathology images, which represent regions of whole digital slides. The procedure can be divided into four main steps: 1) pre-processing with color unmixing and morphological operators, 2) marker-controlled watershed segmentation at multiple scales and with different markers, 3) post-processing for rejection of false regions and 4) merging of the results from multiple scales. The procedure was developed on a set of 21 breast cancer cases (subset A) and tested on a separate validation set of 18 cases (subset B). The evaluation was done in terms of both detection accuracy (sensitivity and positive predictive value) and segmentation accuracy (Dice coefficient). The mean estimated sensitivity for subset A was 0.875 (±0.092) and for subset B 0.853 (±0.077). The mean estimated positive predictive value was 0.904 (±0.075) and 0.886 (±0.069) for subsets A and B, respectively. For both subsets, the distribution of the Dice coefficients had a high peak around 0.9, with the vast majority of segmentations having values larger than 0.8. © 2013 Veta et al

Knee Images Digital Analysis (KIDA): a novel method to quantify individual radiographic features of knee osteoarthritis in detail

SummaryObjectiveRadiography is still the golden standard for imaging features of osteoarthritis (OA), such as joint space narrowing, subchondral sclerosis, and osteophyte formation. Objective assessment, however, remains difficult. The goal of the present study was to evaluate a novel digital method to analyse standard knee radiographs.MethodsStandardized radiographs of 20 healthy and 55 OA knees were taken in general practise according to the semi-flexed method by Buckland-Wright. Joint Space Width (JSW), osteophyte area, subchondral bone density, joint angle, and tibial eminence height were measured as continuous variables using newly developed Knee Images Digital Analysis (KIDA) software on a standard PC.Two observers evaluated the radiographs twice, each on two different occasions. The observers were blinded to the source of the radiographs and to their previous measurements. Statistical analysis to compare measurements within and between observers was performed according to Bland and Altman. Correlations between KIDA data and Kellgren & Lawrence (K&L) grade were calculated and data of healthy knees were compared to those of OA knees.ResultsIntra- and inter-observer variations for measurement of JSW, subchondral bone density, osteophytes, tibial eminence, and joint angle were small. Significant correlations were found between KIDA parameters and K&L grade. Furthermore, significant differences were found between healthy and OA knees.ConclusionIn addition to JSW measurement, objective evaluation of osteophyte formation and subchondral bone density is possible on standard radiographs. The measured differences between OA and healthy individuals suggest that KIDA allows detection of changes in time, although sensitivity to change has to be demonstrated in long-term follow-up studies

Appearance Matters: Neural Correlates of Food Choice and Packaging Aesthetics

Neuro-imaging holds great potential for predicting choice behavior from brain responses. In this study we used both traditional mass-univariate and state-of-the-art multivariate pattern analysis to establish which brain regions respond to preferred packages and to what extent neural activation patterns can predict realistic low-involvement consumer choices. More specifically, this was assessed in the context of package-induced binary food choices. Mass-univariate analyses showed that several regions, among which the bilateral striatum, were more strongly activated in response to preferred food packages. Food choices could be predicted with an accuracy of up to 61.2% by activation patterns in brain regions previously found to be involved in healthy food choices (superior frontal gyrus) and visual processing (middle occipital gyrus). In conclusion, this study shows that mass-univariate analysis can detect small package-induced differences in product preference and that MVPA can successfully predict realistic low-involvement consumer choices from functional MRI data