MRI2MRI weights for transformations between T1-weighted and T2-weighted MRI images
| dc.contributor.author | Xiao, Sa | |
| dc.contributor.author | Lee, Aaron | |
| dc.contributor.author | Rokem, Ariel | |
| dc.date.accessioned | 2019-09-07T04:45:51Z | |
| dc.date.available | 2019-09-07T04:45:51Z | |
| dc.date.issued | 2019-09-06 | |
| dc.description | These are the learned pytorch weights for these transformations | en_US |
| dc.description.abstract | Different brain MRI contrasts represent different tissue properties and are sensitive to different artifacts. The relationship between different contrasts is therefore complex and nonlinear. We developed a deep convolutional network that learns the mapping between different MRI contrasts. Using a publicly available dataset, we demonstrate that this algorithm accurately transforms between T1- and T2-weighted images, proton density images, time-of-flight angiograms, and diffusion MRI images. We demonstrate that these transformed images can be used to improve spatial registration between MR images of different contrasts. | en_US |
| dc.identifier.uri | http://hdl.handle.net/1773/44486 | |
| dc.rights | CC0 1.0 Universal | * |
| dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | * |
| dc.title | MRI2MRI weights for transformations between T1-weighted and T2-weighted MRI images | en_US |
| dc.type | Dataset | en_US |
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