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.idea/.gitignore

@@ -0,0 +1,10 @@
+# Default ignored files
+/shelf/
+/workspace.xml
+# Ignored default folder with query files
+/queries/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml
+# Editor-based HTTP Client requests
+/httpRequests/

.idea/FDG-NeuroSegmenter.iml

@@ -0,0 +1,8 @@
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+    <inspection_tool class="PyStubPackagesAdvertiser" enabled="true" level="WARNING" enabled_by_default="true">
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+          <option value="pandas" />
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.idea/inspectionProfiles/profiles_settings.xml

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.idea/misc.xml

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.idea/modules.xml

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.idea/vcs.xml

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+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
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README.md

@@ -1,3 +1,30 @@
+---
+license: mit
+tags:
+
+- medical
+
+- neuroimaging
+
+- fdg-pet
+
+- brain-segmentation
+
+- deep-learning
+
+- 3d-segmentation
+datasets:
+
+- adni
+
+- nacc
+
+- oasis3
+
+- nifd
+pipeline_tag: image-segmentation
+library_name: pytorch
+---
 # FDG-NeuroSegmenter
 <b>FDG-NeuroSegmenter</b> is a deep-learning-based model developed to perform the automatic segmentation of 52 
 anatomical regions in brain [<sup>18</sup>F]FDG PET images.
@@ -5,7 +32,6 @@ anatomical regions in brain [<sup>18</sup>F]FDG PET images.
 Here you can find the [nnU-Net](https://github.com/MIC-DKFZ/nnUNet) models! For more information and other resources
 check out the [repository on GitHub](https://github.com/NM-Radiopharmacology/FDG-NeuroSegmenter.git).
 
-
 If you use the FDG-NeuroSegmenter models in your research, please cite our paper:
 > **Brain Fluorodeoxyglucose PET Anatomical Segmentation via AI: Extensive Validation in the Neurodegenerative Spectrum**  
 > Luísa C. Silva, Francisco P. M. Oliveira and Durval C. Costa for the Alzheimer's Disease Neuroimaging Initiative and for the Frontotemporal Lobar Degeneration Neuroimaging Initiative