Paper
29 March 2013 A visualization platform for high-throughput, follow-up, co-registered multi-contrast MRI rat brain data
A. Khmelinskii, L. Mengler, P. Kitslaar, M. Staring, M. Hoehn, B. P. F. Lelieveldt
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Abstract
Multi-contrast MRI is a frequently used imaging technique in preclinical brain imaging. In longitudinal cross-sectional studies exploring and browsing through this high-throughput, heterogeneous data can become a very demanding task. The goal of this work was to build an intuitive and easy to use, dedicated visualization and side-by-side exploration tool for heterogeneous, co-registered multi-contrast, follow-up cross-sectional MRI data. The deformation field, which results from the registration step, was used to automatically link the same voxel in the displayed datasets of interest. Its determinant of the Jacobian (detJac) was used for a faster and more accurate visual assessment and comparison of brain deformation between the follow-up scans. This was combined with an efficient data management scheme. We investigated the functionality and the utility of our tool in the neuroimaging research field by means of a case study evaluation with three experienced domain scientists, using longitudinal, cross-sectional multi-contrast MRI rat brain data. Based on the performed case study evaluation we can conclude that the proposed tool improves the visual assessment of high-throughput cross-sectional, multi-contrast, follow-up data and can further assist in guiding quantitative studies.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. Khmelinskii, L. Mengler, P. Kitslaar, M. Staring, M. Hoehn, and B. P. F. Lelieveldt "A visualization platform for high-throughput, follow-up, co-registered multi-contrast MRI rat brain data", Proc. SPIE 8672, Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging, 86721W (29 March 2013); https://doi.org/10.1117/12.2006529
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Cited by 3 scholarly publications.
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KEYWORDS
Brain

Visualization

Magnetic resonance imaging

Image registration

Neuroimaging

Diffusion tensor imaging

Data modeling

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