YMCA &amp;#x2014; Your mesh comparison application

Schmidt, Johanna; Preiner, Reinhold; Auzinger, Thomas; Wimmer, Michael; Gröller, M. Eduard; Brückner, Stefan

doi:10.1109/vast.2014.7042491

Cited by 17 publications

(8 citation statements)

References 24 publications

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“…Tory et al [49] investigate a superposition approach for the development of brain lesions extracted at different time points from MRI images. The use of explicit encoding to highlight structural differences is used by Schmidt et al [50], where they compare a large number of similar meshes and can quickly identify regions of differences in multiple linked views.…”

mentioning

confidence: 99%

VAPOR: Visual Analytics for the Exploration of Pelvic Organ Variability in Radiotherapy

Furmanová

Großmann

Muren

et al. 2020

Computers & Graphics

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mentioning

confidence: 99%

VAPOR: Visual Analytics for the Exploration of Pelvic Organ Variability in Radiotherapy

Furmanová

Großmann

Muren

et al. 2020

Computers & Graphics

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“…van Pelt et al [39] presented an intuitive details-on-demand glyph set for comparatively visualizing wall-shear stresses between different stent configurations. Schmidt et al [33] introduced a comparative visual analysis system for multiple 3D meshes that combines explicit encoding, juxtaposition, and parallel coordinate plots for quantitative measures. However, few methods are designed specifically for diffusion tensor fields.…”

Section: Comparative Visualizationmentioning

confidence: 99%

Glyph-Based Comparative Visualization for Diffusion Tensor Fields

Zhang

Schultz

Lawonn

et al. 2016

IEEE Trans. Visual. Comput. Graphics

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Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging modality that enables the in-vivo reconstruction and visualization of fibrous structures. To inspect the local and individual diffusion tensors, glyph-based visualizations are commonly used since they are able to effectively convey full aspects of the diffusion tensor. For several applications it is necessary to compare tensor fields, e.g., to study the effects of acquisition parameters, or to investigate the influence of pathologies on white matter structures. This comparison is commonly done by extracting scalar information out of the tensor fields and then comparing these scalar fields, which leads to a loss of information. If the glyph representation is kept, simple juxtaposition or superposition can be used. However, neither facilitates the identification and interpretation of the differences between the tensor fields. Inspired by the checkerboard style visualization and the superquadric tensor glyph, we design a new glyph to locally visualize differences between two diffusion tensors by combining juxtaposition and explicit encoding. Because tensor scale, anisotropy type, and orientation are related to anatomical information relevant for DTI applications, we focus on visualizing tensor differences in these three aspects. As demonstrated in a user study, our new glyph design allows users to efficiently and effectively identify the tensor differences. We also apply our new glyphs to investigate the differences between DTI datasets of the human brain in two different contexts using different b-values, and to compare datasets from a healthy and HIV-infected subject.

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“…Migut et al [19] present approaches for metrics considering nominal attributes and weights. Mesh comparison metrics, as presented by Schmidt et al [27], allow the integration of the geometric part of the data into the similarity computation.…”

Section: Similarity-based Analysismentioning

confidence: 99%

Visual analytics and rendering for tunnel crack analysis

et al. 2016

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The visual analysis of surface cracks plays an essential role in tunnel maintenance when assessing the condition of a tunnel. To identify patterns of cracks, which endanger the structural integrity of its concrete surface, analysts need an integrated solution for visual analysis of geometric and multivariate data to decide if issuing a repair project is necessary. The primary contribution of this work is a design study, supporting tunnel crack analysis by tightly integrating geometric and attribute views to allow users a holistic visual analysis of geometric representations and multivariate attributes. Our secondary contribution is Visual Analytics and Rendering, a methodological approach which addresses challenges and recurring design questions in integrated systems. We evaluated the tunnel crack analysis solution in informal feedback sessions with experts from tunnel maintenance and surveying. We substantiated the derived methodology by providing guidelines and linking it to examples from the literature.

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YMCA — Your mesh comparison application

Cited by 17 publications

References 24 publications

VAPOR: Visual Analytics for the Exploration of Pelvic Organ Variability in Radiotherapy

VAPOR: Visual Analytics for the Exploration of Pelvic Organ Variability in Radiotherapy

Glyph-Based Comparative Visualization for Diffusion Tensor Fields

Visual analytics and rendering for tunnel crack analysis

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