Visual representations of isosurfaces are ubiquitous in the scientific and engineering literature. In this paper, we present techniques to assess the behavior of isosurface extraction codes. Where applicable, these techniques allow us to distinguish whether anomalies in isosurface features can be attributed to the underlying physical process or to artifacts from the extraction process. Such scientific scrutiny is at the heart of verifiable visualization--subjecting visualization algorithms to the same verification process that is used in other components of the scientific pipeline. More concretely, we derive formulas for the expected order of accuracy (or convergence rate) of several isosurface features, and compare them to experimentally observed results in the selected codes. This technique is practical: in two cases, it exposed actual problems in implementations. We provide the reader with the range of responses they can expect to encounter with isosurface techniques, both under "normal operating conditions" and also under adverse conditions. Armed with this information--the results of the verification process--practitioners can judiciously select the isosurface extraction technique appropriate for their problem of interest, and have confidence in its behavior.
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http://dx.doi.org/10.1109/TVCG.2009.194 | DOI Listing |
IEEE Trans Vis Comput Graph
September 2024
This paper presents a practical approach for the optimization of topological simplification, a central pre-processing step for the analysis and visualization of scalar data. Given an input scalar field f and a set of "signal" persistence pairs to maintain, our approaches produces an output field g that is close to f and which optimizes (i) the cancellation of "non-signal" pairs, while (ii) preserving the "signal" pairs. In contrast to pre-existing simplification algorithms, our approach is not restricted to persistence pairs involving extrema and can thus address a larger class of topological features, in particular saddle pairs in three-dimensional scalar data.
View Article and Find Full Text PDFMolecules
August 2024
Department of Natural Sciences, Santa Fe College, Gainesville, FL 32066, USA.
In this research work, we examined the decomposition mechanisms of -substituted diacetamides. We focused on the substituent effect on the nitrogen lone-pair electron delocalization, with electron-withdrawing and electron donor groups. DFT functionals used the following: B1LYP, B3PW91, CAMB3LYP, LC-BLYP, and X3LYP.
View Article and Find Full Text PDFMed Eng Phys
August 2024
Department of Applied Mechanics and Biomedical Engineering, Indian Institute of Technology Madras, Chennai, 600036, India. Electronic address:
Background And Objective: Imaging methodologies such as, computed tomography (CT) aid in three-dimensional (3D) reconstruction of patient-specific aneurysms. The radiological data is useful in understanding their location, shape, size, and disease progression. However, there are serious impediments in discerning the blood vessel wall thickness due to limitations in the current imaging modalities.
View Article and Find Full Text PDFIEEE Trans Vis Comput Graph
August 2024
Neural implicit function based on signed distance field (SDF) has achieved impressive progress in reconstructing 3D models with high fidelity. However, such approaches can only represent closed surfaces. Recent works based on unsigned distance function (UDF) are proposed to handle both watertight and single-layered open surfaces.
View Article and Find Full Text PDFIEEE Trans Vis Comput Graph
June 2024
New web technologies have enabled the deployment of powerful GPU-based computational pipelines that run entirely in the web browser, opening a new frontier for accessible scientific visualization applications. However, these new capabilities do not address the memory constraints of lightweight end-user devices encountered when attempting to visualize the massive data sets produced by today's simulations and data acquisition systems. We propose a novel implicit isosurface rendering algorithm for interactive visualization of massive volumes within a small memory footprint.
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