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Improving T1 Model Selection #227
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Improving T1 Model Selection #227
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Hello @alexdaniel654, thank you for updating!
Comment last updated at 2024-09-30 12:57:07 UTC |
Because codecov isn't working... again...
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## dev #227 +/- ##
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- Coverage 97.97% 97.96% -0.02%
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Files 48 48
Lines 4445 4470 +25
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+ Hits 4355 4379 +24
- Misses 90 91 +1 ☔ View full report in Codecov by Sentry. |
Proposed changes
Pre-processing steps (registration, EPI distortion correction etc) can often cause quite a lot of slightly negative numbers, this then means the T1 mapping code assumes the data has been magnitude corrected. After multiple people have had issues when trying to debug this behaviour we've decided it makes sense to add a flag when instantiating the class to select if the data should be fit to a magnitude corrected model or absolute model.
auto
model selection now considers data to have been magnitude corrected if 5% of the voxels of the first inversion are less than -0.05 x the 95th percentile of the signal in the final inversion time i.e. the number of negative voxels required for the signal to be considered magnitude corrected has increased and the threshold at which voxels are considered negative is now based on the dynamic range of the data so floating point errors shouldn't cause voxels with an intensity of -1E-6 to be considered negative any more.Should close #225
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