Paper
13 March 2009 Locally homogenized and de-noised vector fields for cardiac fiber tracking in DT-MRI images
Alireza Akhbardeh, Fijoy Vadakkumpadan, Jason Bayer, Natalia A. Trayanova
Author Affiliations +
Abstract
In this study we develop a methodology to accurately extract and visualize cardiac microstructure from experimental Diffusion Tensor (DT) data. First, a test model was constructed using an image-based model generation technique on Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) data. These images were derived from a dataset having 122x122x500 um3 voxel resolution. De-noising and image enhancement was applied to this high-resolution dataset to clearly define anatomical boundaries within the images. The myocardial tissue was segmented from structural images using edge detection, region growing, and level set thresholding. The primary eigenvector of the diffusion tensor for each voxel, which represents the longitudinal direction of the fiber, was calculated to generate a vector field. Then an advanced locally regularizing nonlinear anisotropic filter, termed Perona-Malik (PEM), was used to regularize this vector field to eliminate imaging artifacts inherent to DT-MRI from volume averaging of the tissue with the surrounding medium. Finally, the vector field was streamlined to visualize fibers within the segmented myocardial tissue to compare the results with unfiltered data. With this technique, we were able to recover locally regularized (homogenized) fibers with a high accuracy by applying the PEM regularization technique, particularly on anatomical surfaces where imaging artifacts were most apparent. This approach not only aides in the visualization of noisy complex 3D vector fields obtained from DT-MRI, but also eliminates volume averaging artifacts to provide a realistic cardiac microstructure for use in electrophysiological modeling studies.
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Alireza Akhbardeh, Fijoy Vadakkumpadan, Jason Bayer, and Natalia A. Trayanova "Locally homogenized and de-noised vector fields for cardiac fiber tracking in DT-MRI images", Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72611R (13 March 2009); https://doi.org/10.1117/12.811629
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KEYWORDS
Diffusion

Visualization

Image segmentation

Tissues

Data modeling

Heart

3D modeling

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