Fused DTI/HARDI visualization.
High-angular resolution diffusion imaging (HARDI) is a diffusion weighted MRI technique that overcomes some of the decisive limitations of its predecessor, diffusion tensor imaging (DTI), in the areas of composite nerve fiber structure. Despite its advantages, HARDI raises several issues: complex modeling of the data, nonintuitive and computationally demanding visualization, inability to interactively explore and transform the data, etc. To overcome these drawbacks, we present a novel, multifield visualization framework that adopts the benefits of both DTI and HARDI. By applying a classification scheme based on HARDI anisotropy measures, the most suitable model per imaging voxel is automatically chosen. This classification allows simplification of the data in areas with single fiber bundle coherence. To accomplish fast and interactive visualization for both HARDI and DTI modalities, we exploit the capabilities of modern GPUs for glyph rendering and adopt DTI fiber tracking in suitable regions. The resulting framework, allows user-friendly data exploration of fused HARDI and DTI data. Many incorporated features such as sharpening, normalization, maxima enhancement and different types of color coding of the HARDI glyphs, simplify the data and enhance its features. We provide a qualitative user evaluation that shows the potentials of our visualization tools in several HARDI applications.
Biomedical Image Analysis Group, Department of Biomedical Engineering, Technische Universiteit Eindhoven, MB 5600, Eindhoven, The Netherlands. vesna.prckovska@gmail.com
Vesna
V
Prčkovska
Tim H J M
TH
Peeters
Markus
M
van Almsick
Bart ter Haar
Bt
Romeny
Anna
A
Vilanova
D000328:Adult; D000465:Algorithms; D000818:Animals; D016880:Anisotropy; D001921:Brain / Q000033:anatomy & histology; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D009412:Nerve Fibers; D019047:Phantoms, Imaging; D051381:Rats; D015203:Reproducibility of Results