Mercurial > repos > PredictPDPS / changeset

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@@ -59,3 +59,10 @@
 
 or any of `demo_denoisingZ()` for image stabilisation experiments and `demo_petZ()` for dynamic PET reconstruction where `Z=1` for Dual Scaling, `Z=2` for Greedy, `Z=3` for No Prediction, `Z=4` for Primal Only, `Z=5` for Proximal, and `Z=6` for Rotation predictors.
 
+## Data sources
+
+The lighthouse image is from the free [Kodak Lossless True Color Image Suite](https://r0k.us/graphics/kodak/). It is loaded via the Julia `TestImages` package.
+
+The file `phantom_slice.mat` is extracted, as described in `phantom_slice.md`, from
+
+* Belzunce, M. A. (2018). High-Resolution Heterogeneous Digital PET [18F]FDG Brain Phantom based on the BigBrain Atlas (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.1190598

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+++ b/src/PET/phantom_slice.md	Fri May 03 17:17:16 2024 +0300
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+# About the phantom slice
+
+The file `phantom_slice.mat` is generated from the file `phantom_atlas_density_cls.mat` of
+
+* Belzunce, M. A. (2018). High-Resolution Heterogeneous Digital PET [18F]FDG Brain Phantom based on the BigBrain Atlas (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.1190598
+
+The following Matlab code does the extraction:
+
+```matlab
+load('phantom_atlas_density_cls.mat')
+fdgPhantom = phantom_atlas_density_cls.phantom;
+slice = 280;
+data = fdgPhantom(:,:,slice);
+imwrite(data, 'phantom_slice.png');
+save 'phantom_slice.mat' data;
+```