128,997 research outputs found
Rendering techniques for multimodal data
Many different direct volume rendering methods have been developed to visualize 3D scalar fields on uniform rectilinear grids. However, little work has been done on rendering simultaneously various properties of the same 3D region measured with different registration devices or at different instants of time. The demand for this type of visualization is rapidly increasing in scientific applications such as medicine in which the visual integration of multiple modalities allows a better comprehension of the anatomy and a perception of its relationships with activity. This paper presents different strategies of Direct Multimodal Volume Rendering (DMVR). It is restricted to voxel models with a known 3D rigid alignment transformation. The paper evaluates at which steps of the render-ing pipeline must the data fusion be realized in order to accomplish the desired visual integration and to provide fast re-renders when some fusion parameters are modified. In addition, it analyzes how existing monomodal visualization al-gorithms can be extended to multiple datasets and it compares their efficiency and their computational cost.Postprint (published version
Direct visualization of aging in colloidal glasses
We use confocal microscopy to directly visualize the dynamics of aging
colloidal glasses. We prepare a colloidal suspension at high density, a simple
model system which shares many properties with other glasses, and initiate
experiments by stirring the sample. We follow the motion of several thousand
colloidal particles after the stirring and observe that their motion
significantly slows as the sample ages. The aging is both spatially and
temporally heterogeneous. Furthermore, while the characteristic relaxation time
scale grows with the age of the sample, nontrivial particle motions continue to
occur on all time scales.Comment: submitted to proceedings for Liquid Matter Conference 200
Adaptive transfer functions: improved multiresolution visualization of medical models
The final publication is available at Springer via http://dx.doi.org/10.1007/s00371-016-1253-9Medical datasets are continuously increasing in size. Although larger models may be available for certain research purposes, in the common clinical practice the models are usually of up to 512x512x2000 voxels. These resolutions exceed the capabilities of conventional GPUs, the ones usually found in the medical doctors’ desktop PCs. Commercial solutions typically reduce the data by downsampling the dataset iteratively until it fits the available target specifications. The data loss reduces the visualization quality and this is not commonly compensated with other actions that might alleviate its effects. In this paper, we propose adaptive transfer functions, an algorithm that improves the transfer function in downsampled multiresolution models so that the quality of renderings is highly improved. The technique is simple and lightweight, and it is suitable, not only to visualize huge models that would not fit in a GPU, but also to render not-so-large models in mobile GPUs, which are less capable than their desktop counterparts. Moreover, it can also be used to accelerate rendering frame rates using lower levels of the multiresolution hierarchy while still maintaining high-quality results in a focus and context approach. We also show an evaluation of these results based on perceptual metrics.Peer ReviewedPostprint (author's final draft
Clogging by sieving in microchannels: Application to the detection of contaminants in colloidal suspensions
We report on a microfluidic method that allows measurement of a small
concentration of large contaminants in suspensions of solid micrometer-scale
particles. To perform the measurement, we flow the colloidal suspension through
a series of constrictions, i.e. a microchannel of varying cross-section. We
show and quantify the role of large contaminants in the formation of clogs at a
constriction and the growth of the resulting filter cake. By measuring the time
interval between two clogging events in an array of parallel microchannels, we
are able to estimate the concentration of contaminants whose size is selected
by the geometry of the microfluidic device. This technique for characterizing
colloidal suspensions offers a versatile and rapid tool to explore the role of
contaminants on the properties of the suspensions
A Multi-Code Analysis Toolkit for Astrophysical Simulation Data
The analysis of complex multiphysics astrophysical simulations presents a
unique and rapidly growing set of challenges: reproducibility, parallelization,
and vast increases in data size and complexity chief among them. In order to
meet these challenges, and in order to open up new avenues for collaboration
between users of multiple simulation platforms, we present yt (available at
http://yt.enzotools.org/), an open source, community-developed astrophysical
analysis and visualization toolkit. Analysis and visualization with yt are
oriented around physically relevant quantities rather than quantities native to
astrophysical simulation codes. While originally designed for handling Enzo's
structure adaptive mesh refinement (AMR) data, yt has been extended to work
with several different simulation methods and simulation codes including Orion,
RAMSES, and FLASH. We report on its methods for reading, handling, and
visualizing data, including projections, multivariate volume rendering,
multi-dimensional histograms, halo finding, light cone generation and
topologically-connected isocontour identification. Furthermore, we discuss the
underlying algorithms yt uses for processing and visualizing data, and its
mechanisms for parallelization of analysis tasks.Comment: 18 pages, 6 figures, emulateapj format. Resubmitted to Astrophysical
Journal Supplement Series with revisions from referee. yt can be found at
http://yt.enzotools.org
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2D Visualization of the Psoriasis Transcriptome Fails to Support the Existence of Dual-Secreting IL-17A/IL-22 Th17 T Cells.
The present paradigm of psoriasis pathogenesis revolves around the IL-23/IL-17A axis. Dual-secreting Th17 T cells presumably are the predominant sources of the psoriasis phenotype-driving cytokines, IL-17A and IL-22. We thus conducted a meta-analysis of independently acquired RNA-seq psoriasis datasets to explore the relationship between the expression of IL17A and IL22. This analysis failed to support the existence of dual secreting IL-17A/IL-22 Th17 cells as a major source of these cytokines. However, variable relationships amongst the expression of psoriasis susceptibility genes and of IL17A, IL22, and IL23A were identified. Additionally, to shed light on gene expression relationships in psoriasis, we applied a machine learning nonlinear dimensionality reduction strategy (t-SNE) to display the entire psoriasis transcriptome as a 2-dimensonal image. This analysis revealed a variety of gene clusters, relevant to psoriasis pathophysiology but failed to support a relationship between IL17A and IL22. These results support existing theories on alternative sources of IL-17A and IL-22 in psoriasis such as a Th22 cells and non-T cell populations
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