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1.
IEEE Comput Graph Appl ; 34(5): 70-82, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25248201

RESUMO

Medical cohort studies enable the study of medical hypotheses with many samples. Often, these studies acquire a large amount of heterogeneous data from many subjects. Usually, researchers study a specific data subset to confirm or reject specific hypotheses. A new approach enables the interactive visual exploration and analysis of such data, helping to generate and validate hypotheses. A data-cube-based model handles partially overlapping data subsets during the interactive visualization. This model enables seamless integration of the heterogeneous data and the linking of spatial and nonspatial views of the data. Researchers implemented this model in a prototype application and used it to analyze data acquired in a cohort study on cognitive aging. Case studies employed the prototype to study aspects of brain connectivity, demonstrating the model's potential and flexibility.


Assuntos
Biologia Computacional/métodos , Gráficos por Computador , Bases de Dados Factuais , Interface Usuário-Computador , Estudos de Coortes , Humanos , Modelos Teóricos
2.
IEEE Trans Vis Comput Graph ; 20(5): 686-701, 2014 May.
Artigo em Inglês | MEDLINE | ID: mdl-26357292

RESUMO

Understanding the hemodynamics of blood flow in vascular pathologies such as intracranial aneurysms is essential for both their diagnosis and treatment. Computational fluid dynamics (CFD) simulations of blood flow based on patient-individual data are performed to better understand aneurysm initiation and progression and more recently, for predicting treatment success. In virtual stenting, a flow-diverting mesh tube (stent) is modeled inside the reconstructed vasculature and integrated in the simulation. We focus on steady-state simulation and the resulting complex multiparameter data. The blood flow pattern captured therein is assumed to be related to the success of stenting. It is often visualized by a dense and cluttered set of streamlines.We present a fully automatic approach for reducing visual clutter and exposing characteristic flow structures by clustering streamlines and computing cluster representatives. While individual clustering techniques have been applied before to streamlines in 3D flow fields, we contribute a general quantitative and a domain-specific qualitative evaluation of three state-of-the-art techniques. We show that clustering based on streamline geometry as well as on domain-specific streamline attributes contributes to comparing and evaluating different virtual stenting strategies. With our work, we aim at supporting CFD engineers and interventional neuroradiologists.


Assuntos
Velocidade do Fluxo Sanguíneo , Imageamento Tridimensional/métodos , Aneurisma Intracraniano/fisiopatologia , Aneurisma Intracraniano/terapia , Modelos Cardiovasculares , Stents , Prótese Vascular , Simulação por Computador , Humanos , Aneurisma Intracraniano/patologia , Resistência ao Cisalhamento , Estresse Mecânico , Terapia Assistida por Computador/métodos
3.
IEEE Trans Vis Comput Graph ; 17(12): 1882-91, 2011 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-22034305

RESUMO

In Toponomics, the function protein pattern in cells or tissue (the toponome) is imaged and analyzed for applications in toxicology, new drug development and patient-drug-interaction. The most advanced imaging technique is robot-driven multi-parameter fluorescence microscopy. This technique is capable of co-mapping hundreds of proteins and their distribution and assembly in protein clusters across a cell or tissue sample by running cycles of fluorescence tagging with monoclonal antibodies or other affinity reagents, imaging, and bleaching in situ. The imaging results in complex multi-parameter data composed of one slice or a 3D volume per affinity reagent. Biologists are particularly interested in the localization of co-occurring proteins, the frequency of co-occurrence and the distribution of co-occurring proteins across the cell. We present an interactive visual analysis approach for the evaluation of multi-parameter fluorescence microscopy data in toponomics. Multiple, linked views facilitate the definition of features by brushing multiple dimensions. The feature specification result is linked to all views establishing a focus+context visualization in 3D. In a new attribute view, we integrate techniques from graph visualization. Each node in the graph represents an affinity reagent while each edge represents two co-occurring affinity reagent bindings. The graph visualization is enhanced by glyphs which encode specific properties of the binding. The graph view is equipped with brushing facilities. By brushing in the spatial and attribute domain, the biologist achieves a better understanding of the function protein patterns of a cell. Furthermore, an interactive table view is integrated which summarizes unique fluorescence patterns. We discuss our approach with respect to a cell probe containing lymphocytes and a prostate tissue section.


Assuntos
Gráficos por Computador , Microscopia de Fluorescência/estatística & dados numéricos , Proteômica/estatística & dados numéricos , Interpretação Estatística de Dados , Humanos , Imageamento Tridimensional/estatística & dados numéricos , Linfócitos/metabolismo , Masculino , Proteínas de Neoplasias/metabolismo , Neoplasias da Próstata/metabolismo
4.
IEEE Trans Vis Comput Graph ; 15(2): 205-20, 2009.
Artigo em Inglês | MEDLINE | ID: mdl-19147886

RESUMO

Dynamic contrast-enhanced image data (perfusion data) are used to characterize regional tissue perfusion. Perfusion data consist of a sequence of images, acquired after a contrast agent bolus is applied. Perfusion data are used for diagnostic purposes in oncology, ischemic stroke assessment or myocardial ischemia. The diagnostic evaluation of perfusion data is challenging, since the data is complex and exhibits various artifacts, e.g., motion artifacts. We provide an overview on existing methods to analyze, and visualize CT and MR perfusion data. The integrated visualization of several 2D parameter maps, the 3D visualization of parameter volumes and exploration techniques are discussed. An essential aspect in the diagnosis of perfusion data is the correlation between perfusion data and derived time-intensity curves as well as with other image data, in particular with high resolution morphologic image data. We discuss visualization support with respect to the three major application areas: ischemic stroke diagnosis, breast tumor diagnosis and the diagnosis of coronary heart disease.


Assuntos
Processamento Eletrônico de Dados/métodos , Processamento de Imagem Assistida por Computador/métodos , Imagem de Perfusão/métodos , Encéfalo/diagnóstico por imagem , Gráficos por Computador , Coração/diagnóstico por imagem , Humanos , Imageamento por Ressonância Magnética , Modelos Cardiovasculares , Tomografia Computadorizada de Emissão , Interface Usuário-Computador
5.
IEEE Trans Med Imaging ; 27(11): 1592-610, 2008 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-18955175

RESUMO

Current magnetic resonance imaging (MRI) technology allows the determination of patient-individual coronary tree structure, detection of infarctions, and assessment of myocardial perfusion. Joint inspection of these three aspects yields valuable information for therapy planning, e.g., through classification of myocardium into healthy tissue, regions showing a reversible hypoperfusion, and infarction with additional information on the corresponding supplying artery. Standard imaging protocols normally provide image data with different orientations, resolutions and coverages for each of the three aspects, which makes a direct comparison of analysis results difficult. The purpose of this work is to develop methods for the alignment and combined analysis of these images. The proposed approach is applied to 21 datasets of healthy and diseased patients from the clinical routine. The evaluation shows that, despite limitations due to typical MRI artifacts, combined inspection is feasible and can yield clinically useful information.


Assuntos
Artefatos , Angiografia Coronária/métodos , Doença da Artéria Coronariana/diagnóstico por imagem , Imagem Cinética por Ressonância Magnética/métodos , Técnica de Subtração , Meios de Contraste , Circulação Coronária , Ecocardiografia sob Estresse , Gadolínio , Humanos , Cintilografia
6.
IEEE Trans Vis Comput Graph ; 13(6): 1392-9, 2007.
Artigo em Inglês | MEDLINE | ID: mdl-17968089

RESUMO

Perfusion data are dynamic medical image data which characterize the regional blood flow in human tissue. These data bear a great potential in medical diagnosis, since diseases can be better distinguished and detected at an earlier stage compared to static image data. The wide-spread use of perfusion data is hampered by the lack of efficient evaluation methods. For each voxel, a time-intensity curve characterizes the enhancement of a contrast agent. Parameters derived from these curves characterize the perfusion and have to be integrated for diagnosis. The diagnostic evaluation of this multi-field data is challenging and time-consuming due to its complexity. For the visual analysis of such datasets, feature-based approaches allow to reduce the amount of data and direct the user to suspicious areas. We present an interactive visual analysis approach for the evaluation of perfusion data. For this purpose, we integrate statistical methods and interactive feature specification. Correlation analysis and Principal Component Analysis (PCA) are applied for dimensionreduction and to achieve a better understanding of the inter-parameter relations. Multiple, linked views facilitate the definition of features by brushing multiple dimensions. The specification result is linked to all views establishing a focus+context style of visualization in 3D. We discuss our approach with respect to clinical datasets from the three major application areas: ischemic stroke diagnosis, breast tumor diagnosis, as well as the diagnosis of the coronary heart disease (CHD). It turns out that the significance of perfusion parameters strongly depends on the individual patient, scanning parameters, and data pre-processing.


Assuntos
Velocidade do Fluxo Sanguíneo/fisiologia , Vasos Sanguíneos/fisiologia , Gráficos por Computador , Modelos Cardiovasculares , Reologia/métodos , Interface Usuário-Computador , Simulação por Computador , Bases de Dados Factuais , Humanos
7.
IEEE Trans Med Imaging ; 24(4): 540-8, 2005 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-15822811

RESUMO

We present a method for visualizing vasculature based on clinical computed tomography or magnetic resonance data. The vessel skeleton as well as the diameter information per voxel serve as input. Our method adheres to these data, while producing smooth transitions at branchings and closed, rounded ends by means of convolution surfaces. We examine the filter design with respect to irritating bulges, unwanted blending and the correct visualization of the vessel diameter. The method has been applied to a large variety of anatomic trees. We discuss the validation of the method by means of a comparison to other visualization methods. Surface distance measures are carried out to perform a quantitative validation. Furthermore, we present the evaluation of the method which has been accomplished on the basis of a survey by 11 radiologists and surgeons.


Assuntos
Algoritmos , Inteligência Artificial , Vasos Sanguíneos/anatomia & histologia , Gráficos por Computador , Aumento da Imagem/métodos , Interpretação de Imagem Assistida por Computador/métodos , Imageamento Tridimensional/métodos , Simulação por Computador , Modelos Anatômicos , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , Processamento de Sinais Assistido por Computador , Interface Usuário-Computador
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