Update 3d_microstructure.md

3d_microstructure.md

@@ -33,13 +33,13 @@ Our dictionary-based segmentation [Dahl et al., 2020](https://ieeexplore.ieee.or
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 ### Graph-based segmentation
-We have developed novel methods for graph-based segmentation ([Jeppesen et al. 2020](https://ieeexplore.ieee.org/document/9156301) and [Jensen et al. 2020](https://ieeexplore.ieee.org/document/9151036)), implemented efficient graph-based algorithms ([Jeppesen et al. 2021](https://ieeexplore.ieee.org/document/9710633)) and benchmarked existing graph-based algorithms ([Jensen et al. 2022](https://ieeexplore.ieee.org/abstract/document/9763394)). Our methods have been used for analysing large 3D data, for example from samples of [peripheral nerves](https://www.nature.com/articles/s41598-020-64430-5) and [muscle fibres](https://www.nature.com/articles/s41598-022-21741-z).
+We have developed novel methods for graph-based segmentation ([Jeppesen et al. 2020](https://ieeexplore.ieee.org/document/9156301) and [Jensen et al. 2020](https://ieeexplore.ieee.org/document/9151036)), implemented efficient graph-based algorithms ([Jeppesen et al. 2021](https://ieeexplore.ieee.org/document/9710633)) and benchmarked existing graph-based algorithms ([Jensen et al. 2022](https://ieeexplore.ieee.org/abstract/document/9763394)). Our methods have been used for analysing large 3D data, for example from samples of peripheral nerves ([Dahlin et al. 2020](https://www.nature.com/articles/s41598-020-64430-5)) and muscle fibres ([Pingel et al. 2022](https://www.nature.com/articles/s41598-022-21741-z)).
 
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 <img title="Non-overlapping surfaces for segmenting foam" src="images/nos_wh.png" alt="Non-overlapping surfaces for segmenting foam" width="600"/>
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-Segmenting individual foam bubbles in a 3D X-ray CT image of aluminium foam using <a href="https://ieeexplore.ieee.org/document/9151036">NOS</a>.
+Segmenting individual foam bubbles in a 3D X-ray CT image of aluminium foam using approach from <a href="https://ieeexplore.ieee.org/document/9151036">Jensen et al. 2020.</a>.
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 ## People