Update README.md

README.md

@@ -9,7 +9,7 @@
  
 # ⚠️***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 at [arXiv](https://arxiv.org/abs/2211.15717).
+**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>
@@ -49,13 +49,12 @@ python EvaluationScripts/evaluation.py
 Please, consider citing our paper, if you find the work useful:
 <pre>
 @misc{perezdefrutos2022ddmr,
-doi = {10.48550/ARXIV.2211.15717},
-url = {https://arxiv.org/abs/2211.15717},
-author = {de Frutos, Javier Pérez and Pedersen, André and Pelanis, Egidijus and Bouget, David and Survarachakan, Shanmugapriya and Langø, Thomas and Elle, Ole-Jakob and Lindseth, Frank},
-keywords = {Image and Video Processing (eess.IV), Computer Vision and Pattern Recognition (cs.CV), FOS: Electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Computer and information sciences, FOS: Computer and information sciences, I.4.9; I.5.4; J.3; J.6, I.4.9},
 title = {Train smarter, not harder: learning deep abdominal CT registration on scarce data},
-publisher = {arXiv},
+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},
-copyright = {Creative Commons Attribution 4.0 International}}
+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>