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Article Dans Une Revue Algorithms Année : 2020

Structure-Aware Trail Bundling for Large DTI Datasets

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Steven Bouma
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Alexandru Telea
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Résumé

Creating simplified visualizations of large 3D trail sets with limited occlusion and preservation of the main structures in the data is challenging. We address this challenge for the specific context of 3D fiber trails created by DTI tractography. For this, we propose to jointly simplify trails in both the geometric space (by extending and adapting an existing bundling method to handle 3D trails) and in the image space (by proposing several shading and rendering techniques). Our method can handle 3D datasets of hundreds of thousands of trails at interactive rate, has parameters for the most of which good preset values are given, and produces visualizations that have been found, in a small-scale user study involving five medical professionals, to be better in occlusion reduction, conveying the connectivity structure of the brain, and overall clarity than existing methods for the same data. We demonstrate our technique with several real-world public DTI datasets.
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Dates et versions

hal-03641308 , version 1 (14-04-2022)

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Steven Bouma, Christophe Hurter, Alexandru Telea. Structure-Aware Trail Bundling for Large DTI Datasets. Algorithms, 2020, ⟨10.3390/a13120316⟩. ⟨hal-03641308⟩

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