diff --git a/README.md b/README.md
index c9d4ed8..0f5fb1f 100644
--- a/README.md
+++ b/README.md
@@ -7,7 +7,7 @@ This repository contains a stable, older release.  Want the new one?  Go to [Cur
 
 This README file is to accompany code for curve skeletonization of elongated objects that may have noisy surfaces, produced by Amy Tabb and Henry Medeiros as a companion to their paper:
 	*Fast and robust curve skeletonization for real-world elongated objects*
-
+````latex
 @INPROCEEDINGS{Tabb18Fast,
 author={Amy Tabb and Henry Medeiros},
 booktitle={2018 IEEE Winter Conference on Applications of Computer Vision (WACV)},
@@ -16,6 +16,7 @@ year={2018},
 pages={1935-1943},
 doi={10.1109/WACV.2018.00214},
 month={March},}
+````
 
 This paper is also available from arXiv:1702.07619 [cs.CV] [here](https://arxiv.org/pdf/1702.07619.pdf) -- including the supplementary material.  The arxiv version is identical in content to the IEEE version.
 
@@ -23,6 +24,7 @@ This paper is also available from arXiv:1702.07619 [cs.CV] [here](https://arxiv.
 
 The code may be used without restriction. If the results of the code are used as a part of a system described in a publication, we request that the authors cite the published paper at a minimum.  If you use the implementation contained in this github release as a part of a publication, we'd be thrilled if you cited the code release as well.  The citation for the code itself is: 
 
+````latex
 @electronic{tabb2018skel_code,
 author = {Tabb, Amy},
 year = {2018},
@@ -31,10 +33,11 @@ doi = {10.15482/USDA.ADC/1399689},
 owner = {Ag Data Commons},
 howpublished= {\url{http://dx.doi.org/10.15482/USDA.ADC/1399689}}
 } 
+````
 
 (Other citation styles are fine -- this is one that worked for us, but we're not totally happy with it.)
 
-Finally, all organizations have ways of assessing impact, and as someone whose work will never see the light of patenting since I develop algorithms, if this curve skeleton algo is useful to your work in some way and you are able to let me know in a one line email, that would be fabulous.
+**Finally, all organizations have ways of assessing impact, and as someone whose work will never see the light of patenting since I develop algorithms, if this curve skeleton algo is useful to your work in some way and you are able to let me know in a one line email, that would be fabulous.**
 
 # Minimal working examples
 Minimal working examples are available as a part of this Github repository, in the `demo_files` directory.  Also, this release is part of a data release hosted at Ag Data Commons, and more information may be available [there](http://dx.doi.org/10.15482/USDA.ADC/1399689).