Merge remote-tracking branch 'origin/master'

.gitignore

@@ -1 +1,3 @@
-/.idea/
+.idea/
+.vs/
+*__pycache__/

.idea/vcs.xml

@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="VcsDirectoryMappings">
-    <mapping directory="$PROJECT_DIR$" vcs="Git" />
-  </component>
-</project>

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2022 Javier Pérez de Frutos
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,12 +1,75 @@
-# DeepDeformationMapRegistration
-Deep learning powered image to image registration, based on VoxelMorph
+<div align="center">
+    <img src="https://user-images.githubusercontent.com/30429725/204778476-4d24c659-9287-48b8-b616-92016ffcf4f6.svg" alt="drawing" width="600">
+</div>
 
-# Usage
-The core functionality reside in DeepDeformationMapRegistration package, e.g., the augmentation layers, metrics, etc.
+<div align="center">
+
+<h1 align="center">DDMR: Deep Deformation Map Registration</h1>
+<h3 align="center">Train smarter, not harder: learning deep abdominal CT registration on scarce data</h3>
+ 
+# ⚠️***WARNING: Under construction*** 
+
+**DDMR** was developed by SINTEF Health Research. The corresponding manuscript describing the framework has been submitted to [IJCARS](https://www.springer.com/journal/11548) and the preprint is openly available on [arXiv](https://arxiv.org/abs/2211.15717).
+
+ 
+</div>
+
+## 💻 Getting started
+
+1. Setup virtual environment:
+```
+virtualenv -ppython3 venv --clear
+source venv/bin/activate
+```
+
+2. Install requirements:
+```
+pip install -r requirements.txt
+```
+
+## 🏋️‍♂️ Training
 
 Use the "MultiTrain" scripts to launch the trainings, providing the neccesary parameters. Those in the COMET folder accepts a .ini configuration file (see COMET/train_config_files for example configurations).
 
+For instance:
+```
+python TrainingScripts/Train_3d.py
+```
+
+## 🔍 Evaluate
+
 Use Evaluate_network to test the trained models. On the Brain folder, use "Evaluate_network__test_fixed.py" instead.
 
-# Warning
-The code in this repo is in need of a thorough clean and refactoring. So expect the unexpected.
+For instance:
+```
+python EvaluationScripts/evaluation.py
+```
+
+## ✨ How to cite
+Please, consider citing our paper, if you find the work useful:
+<pre>
+@misc{perezdefrutos2022ddmr,
+    title = {Train smarter, not harder: learning deep abdominal CT registration on scarce data},
+    author = {Pérez de Frutos, Javier and Pedersen, André and Pelanis, Egidijus and Bouget, David and Survarachakan, Shanmugapriya and Langø, Thomas and Elle, Ole-Jakob and Lindseth, Frank},
+    year = {2022},
+    doi = {10.48550/ARXIV.2211.15717},
+    publisher = {arXiv},
+    copyright = {Creative Commons Attribution 4.0 International},
+    note = {preprint on arXiv at https://arxiv.org/abs/2211.15717}
+}
+</pre>
+
+## ⭐ Acknowledgements
+This project is based on [VoxelMorph](https://github.com/voxelmorph/voxelmorph) library, and its related publication:
+<pre>
+@article{VoxelMorph2019,
+    title={VoxelMorph: A Learning Framework for Deformable Medical Image Registration}, 
+    author={Balakrishnan, Guha and Zhao, Amy and Sabuncu, Mert R. and Guttag, John and Dalca, Adrian V.},
+    journal={IEEE Transactions on Medical Imaging}, 
+    year={2019},
+    volume={38},
+    number={8},
+    pages={1788-1800},
+    doi={10.1109/TMI.2019.2897538}
+}
+</pre>