Depth-Dependent Halos: Illustrative Rendering of Dense Line Data

Everts, Maarten H.; Bekker, Henk; Roerdink, Jos B. T. M.; Isenberg, Tobias

doi:10.1109/tvcg.2009.138

Cited by 109 publications

(86 citation statements)

References 43 publications

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“…Note that for very dense vascular structures, a large number of cutaways is generated, and the local surface of most visible vessels will not exceed the extent of the vessel itself. In this case, our method would resemble dense line rendering and due to conceptual similarities, only slight modifications would ensure convergence to the illustrative method of Everts et al [10].…”

Section: Cost Functionmentioning

confidence: 99%

Vessel Visualization using Curved Surface Reformation

Auzinger

Mistelbauer

Baclija

et al. 2013

IEEE Trans. Visual. Comput. Graphics

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To analyze the lumen of arbitrarily oriented vessels, Centerline Reformation (CR) has been proposed. Both methods project the vascular structures into 2D image space in order to reconstruct the vessel lumen. In this paper, we propose Curved Surface Reformation (CSR), a technique that computes the vessel lumen fully in 3D. This offers high-quality interactive visualizations of vessel lumina and does not suffer from problems of earlier methods such as ambiguous visibility cues or premature discretization of centerline data. Our method maintains exact visibility information until the final query of the 3D lumina data. We also present feedback from several domain experts.

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Section: Cost Functionmentioning

confidence: 99%

Vessel Visualization using Curved Surface Reformation

Auzinger

Mistelbauer

Baclija

et al. 2013

IEEE Trans. Visual. Comput. Graphics

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“…The lines consist of view-aligned quad-strips extended with halos. The halos are generated during the fragment-shading stage [6].…”

Section: Particle Tracesmentioning

confidence: 99%

Interactive Virtual Probing of 4D MRI Blood-Flow

Pelt

Bescós

Breeuwer

et al. 2011

IEEE Trans. Visual. Comput. Graphics

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Fig. 1. Interactive virtual probe with flow visualization approaches, enabling exploration of cardiovascular 4D MRI blood-flow data. Color in the leftmost rendition encodes the blood-flow vorticity, while color in other renditions conveys the local blood-flow speed.Abstract-Better understanding of hemodynamics conceivably leads to improved diagnosis and prognosis of cardiovascular diseases. Therefore, an elaborate analysis of the blood-flow in heart and thoracic arteries is essential. Contemporary MRI techniques enable acquisition of quantitative time-resolved flow information, resulting in 4D velocity fields that capture the blood-flow behavior. Visual exploration of these fields provides comprehensive insight into the unsteady blood-flow behavior, and precedes a quantitative analysis of additional blood-flow parameters. The complete inspection requires accurate segmentation of anatomical structures, encompassing a time-consuming and hard-to-automate process, especially for malformed morphologies. We present a way to avoid the laborious segmentation process in case of qualitative inspection, by introducing an interactive virtual probe. This probe is positioned semi-automatically within the blood-flow field, and serves as a navigational object for visual exploration. The difficult task of determining position and orientation along the view-direction is automated by a fitting approach, aligning the probe with the orientations of the velocity field. The aligned probe provides an interactive seeding basis for various flow visualization approaches. We demonstrate illustration-inspired particles, integral lines and integral surfaces, conveying distinct characteristics of the unsteady blood-flow. Lastly, we present the results of an evaluation with domain experts, valuing the practical use of our probe and flow visualization techniques.

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“…An Three example stages of filtering, using the fractional anisotropy (FA) value of a DTI fiber tract data set. With the growing filtering threshold for FA, more of the internal structure of the data set is revealed [9].…”

Section: Filtering and Visualization Of Diffusion Tensor Imaging Datamentioning

confidence: 99%

“…This allows the determination and visualization of structural connectivity between brain regions; see Fig. 7 for an example [9]. For connectivity-based morphological filtering and visualization of tensor fields, new developments in (hyper)connectivity, constrained and partial connectivity are of current interest [3,39,44,45,52].…”

Section: Filtering and Visualization Of Diffusion Tensor Imaging Datamentioning

confidence: 99%

Mathematical Morphology in Computer Graphics, Scientific Visualization and Visual Exploration

Roerdink

2011

Mathematical Morphology and Its Applications to Image and Signal Processing

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Abstract. Historically, mathematical morphology has primarily focused on the processing and analysis of two-dimensional image data. In this paper, we survey a number of other areas where mathematical morphology finds fruitful application, such as computer graphics and solid modeling; path planning; filtering, segmentation and visualization of volume data; or visual exploration of high-dimensional data. We also mention techniques for accelerating morphological computations by using graphics hardware (GPU computing).

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Depth-Dependent Halos: Illustrative Rendering of Dense Line Data

Cited by 109 publications

References 43 publications

Vessel Visualization using Curved Surface Reformation

Vessel Visualization using Curved Surface Reformation

Interactive Virtual Probing of 4D MRI Blood-Flow

Mathematical Morphology in Computer Graphics, Scientific Visualization and Visual Exploration

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