Add Citations

readme.md

@@ -7,6 +7,34 @@ It was designed and tested to sharpen soft-labeled classifier outputs for medica
 
 The wrapper makes it very easy to run Krähenbühls super fast DenseCRF on your classifier output (i.e. the output of your fully convolutional neural network) just by a single python method call.
 
+
+This code was used in MICCAI 2016 paper ([arXiv link](https://arxiv.org/abs/1610.02177)) titled : 
+
+```
+Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional 
+Neural Networks and 3D Conditional Random Fields
+```
+
+### Citation ###
+
+If you have used this code in your research please use the following BibTeX for citation :
+```
+@Inbook{Christ2016,
+title="Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields",
+author="Christ, Patrick Ferdinand and Elshaer, Mohamed Ezzeldin A. and Ettlinger, Florian and Tatavarty, Sunil and Bickel, Marc and Bilic, Patrick and Rempfler, Markus and Armbruster, Marco and Hofmann, Felix and D'Anastasi, Melvin and Sommer, Wieland H. and Ahmadi, Seyed-Ahmad and Menze, Bjoern H.",
+editor="Ourselin, Sebastien and Joskowicz, Leo and Sabuncu, Mert R. and Unal, Gozde and Wells, William",
+bookTitle="Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2016: 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II",
+year="2016",
+publisher="Springer International Publishing",
+address="Cham",
+pages="415--423",
+isbn="978-3-319-46723-8",
+doi="10.1007/978-3-319-46723-8_48",
+url="http://dx.doi.org/10.1007/978-3-319-46723-8_48"
+}
+```
+You can find the full code at [https://github.com/IBBM/Cascaded-FCN](https://github.com/IBBM/Cascaded-FCN). 
+
 ## DenseCRF ``denseinference/lib``
 The CRF-code is modified from the publicly available code by Philipp Krähenbühl and Vladlen Koltun.
 See their project [website](http://www.philkr.net/home/densecrf) for more information.