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Abstract #4720

Performant summative 3D rendering of voxel-wise MRF segmentation data

Andrew Dupuis1,2, Debra McGivney3, Rasim Boyacioglu3, Dan Ma3, Anagha Deshmane4, and Mark A Griswold1,2,3

1Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, 2Interactive Commons, Case Western Reserve University, Cleveland, OH, United States, 3Department of Radiology, School of Medicine, Case Western Reserve University, Cleveland, OH, United States, 4Max Planck Institute for Biological Cybernetics, Tübingen, Germany

Visualization of Magnetic Resonance Fingerprinting segmented data presents significant difficulty because of the abstraction from the usual appearance and contrast of MR images. We present a method of rendering any probability-based tissue fraction partial volume ROIs in three dimensions using additive voxelized volumetric rendering as a form of segmentation. Datasets consist of n groups of segmented maps with each voxel representing the probability of a given tissue converted into 3D textures usable by the GPU to perform raymarched additive rendering. This allows for different tissue classifications within the dataset to be faded in and out with minimal human involvement.

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