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

Dupuis, A., McGivney, D., Boyacioglu, R., Ma, D., Deshmane, A., & Griswold, M. (2019). Performant summative 3D rendering of voxel-wise MRF segmentation data. Poster presented at 27th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2019), Montréal, QC, Canada.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-96EA-C Version Permalink: http://hdl.handle.net/21.11116/0000-0003-C756-C
Genre: Poster

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 Creators:
Dupuis, A, Author
McGivney, D, Author
Boyacioglu, R, Author
Ma, D, Author
Deshmane, A1, 2, Author              
Griswold, M, Author
Affiliations:
1Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: 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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 Dates: 2019-05
 Publication Status: Published online
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Title: 27th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2019)
Place of Event: Montréal, QC, Canada
Start-/End Date: 2019-05-11 - 2019-05-16

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Title: ISMRM 27th Annual Meeting & Exhibition
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: 4720 Start / End Page: - Identifier: -