DocumentCode :
2537432
Title :
Fiber stippling: An illustrative rendering for probabilistic diffusion tractography
Author :
Goldau, Mathias ; Wiebel, Alexander ; Gorbach, Nico Stephan ; Melzer, Corina ; Hlawitschka, Mario ; Scheuermann, Gerik ; Tittgemeyer, Marc
fYear :
2011
fDate :
23-24 Oct. 2011
Firstpage :
23
Lastpage :
30
Abstract :
One of the most promising avenues for compiling anatomical brain connectivity data arises from diffusion magnetic resonance imaging (dMRI). dMRI provides a rather novel family of medical imaging techniques with broad application in clinical as well as basic neu-roscience as it offers an estimate of the brain´s fiber structure completely non-invasively and in vivo. A convenient way to reconstruct neuronal fiber pathways and to characterize anatomical connectivity from this data is the computation of diffusion tractograms. In this paper, we present a novel and effective method for visualizing probabilistic tractograms within their anatomical context. Our illustrative rendering technique, called fiber stippling, is inspired by visualization standards as found in anatomical textbooks. These illustrations typically show slice-based projections of fiber pathways and are typically hand-drawn. Applying the automatized technique to diffusion tractography, we demonstrate its expressiveness and intuitive usability as well as a more objective way to present white-matter structure in the human brain.
Keywords :
biodiffusion; biomedical MRI; brain models; data visualisation; medical image processing; probability; rendering (computer graphics); anatomical brain connectivity data; anatomical textbook; dMRI; diffusion magnetic resonance imaging; diffusion tractogram; fiber stippling; medical imaging technique; neu-roscience; neuronal fiber pathway; probabilistic diffusion tractography; rendering technique; slice-based projection; Context; Data visualization; Image resolution; Probabilistic logic; Rendering (computer graphics); Shape; Tensile stress; DTI; Illustrative Visualization; Probabilistic Tractography; Scalar Field Data; Tensor Field Data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biological Data Visualization (BioVis), 2011 IEEE Symposium on
Conference_Location :
Providence, RI
Print_ISBN :
978-1-4673-0003-2
Type :
conf
DOI :
10.1109/BioVis.2011.6094044
Filename :
6094044
Link To Document :
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