Updated README.md with abstract link.

Author: nbwuzhe

README.md

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-[![DOI](https://zenodo.org/badge/424335964.svg)](https://zenodo.org/badge/latestdoi/424335964)
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 # Demonstration Code for Gradient Impulse Response Function (GIRF) Calculation and Analysis
 
+[![DOI](https://zenodo.org/badge/424335964.svg)](https://zenodo.org/badge/latestdoi/424335964)
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 This is the demonstration code of the abstract *MR Gradient System Long-Term Stability Investigation and Protocol Optimization for Quality Control using Gradient Impulse Response Function (GIRF)* by *Zhe Wu, Alexander Jaffray, Johanna Vannesjo, Kamil Uludag, and Lars Kasper* for the Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting, which will be held in London UK, between May 7 - 12, 2022. The full information of this abstract can be found in [references](#references), and the PDF version of the published abstract can be found [here](./docs/PublishedAbstract.pdf).
 
 > Copyright (C) 2021-2022  
@@ -18,7 +18,7 @@ This is the demonstration code of the abstract *MR Gradient System Long-Term Sta
 
 2. In the `main.m` file, change the variables under the section "Set User Parameters". Set the variable `dataPath` as the path that stores all the downloaded data; set the variable `gradientAxis` to the gradient axis that needs to be analysed (choose from 'X', 'Y', and 'Z', **case insensitive**); set the variable `measNum` to the measurement dataset to be analysed (only applicable to `script_OriginGIRFCalculation.m`, see the following section [Script List](#script-list) and the instructions inside this script for details).
 
-3. Run the `main.m` file and all the demo scripts should be executed. You may change the variable `gradientAxis` to check the other gradient axis. 
+3. Run the `main.m` file and all the demo scripts should be executed. You may change the variable `gradientAxis` to check the other gradient axis.
 
 ## Dataset for Demonstration
 
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 ## References
 
 **The Corresponding ISMRM 2022 Abstract to This Repository**
-Wu, Z., Jaffray, A., Vannesjo, S.J., Uludag, K., Kasper, L., 2022. MR System Stability and Quality Control using Gradient Impulse Response Functions (GIRF). Proc. Intl. Soc. Mag. Reson. Med. 30, 0641. 
+Wu, Z., Jaffray, A., Vannesjo, S.J., Uludag, K., Kasper, L., 2022. MR System Stability and Quality Control using Gradient Impulse Response Functions (GIRF). Proc. Intl. Soc. Mag. Reson. Med. 30, 0641. [Link](https://submissions.mirasmart.com/ISMRM2022/itinerary/Files/PDFFiles/0641.html)
 
 **Gradient system characterization**
-Vannesjo, S.J., Haeberlin, M., Kasper, L., Pavan, M., Wilm, B.J., Barmet, C., Pruessmann, K.P., 2013. Gradient system characterization by impulse response measurements with a dynamic field camera. Magn Reson Med 69, 583–593. https://doi.org/10.1002/mrm.24263
+Vannesjo, S.J., Haeberlin, M., Kasper, L., Pavan, M., Wilm, B.J., Barmet, C., Pruessmann, K.P., 2013. Gradient system characterization by impulse response measurements with a dynamic field camera. Magn Reson Med 69, 583–593. [Link](https://doi.org/10.1002/mrm.24263)
 
 **Image reconstruction based on the GIRF characterization**
-Vannesjo, S.J., Graedel, N.N., Kasper, L., Gross, S., Busch, J., Haeberlin, M., Barmet, C., Pruessmann, K.P., 2016. Image reconstruction using a gradient impulse response model for trajectory prediction. Magn Reson Med 76, 45–58. https://doi.org/10.1002/mrm.25841
+Vannesjo, S.J., Graedel, N.N., Kasper, L., Gross, S., Busch, J., Haeberlin, M., Barmet, C., Pruessmann, K.P., 2016. Image reconstruction using a gradient impulse response model for trajectory prediction. Magn Reson Med 76, 45–58. [Link](https://doi.org/10.1002/mrm.25841)
 
 **GIRF-based spiral fMRI**
-Graedel, N.N., Kasper, L., Engel, M., Nussbaum, J., Wilm, B.J., Pruessmann, K.P., Vannesjo, S.J., 2019. Feasibility of spiral fMRI based on an LTI gradient model. bioRxiv 805580. https://doi.org/10.1101/805580
+Graedel, N.N., Kasper, L., Engel, M., Nussbaum, J., Wilm, B.J., Pruessmann, K.P., Vannesjo, S.J., 2019. Feasibility of spiral fMRI based on an LTI gradient model. bioRxiv 805580. [Link](https://doi.org/10.1101/805580)
 
 **GIRF-based pre-emphasis of gradient or shim channels**
-Vannesjo, S.J., Duerst, Y., Vionnet, L., Dietrich, B.E., Pavan, M., Gross, S., Barmet, C., Pruessmann, K.P., 2017. Gradient and shim pre-emphasis by inversion of a linear time-invariant system model. Magn Reson Med 78, 1607–1622. https://doi.org/10.1002/mrm.26531
+Vannesjo, S.J., Duerst, Y., Vionnet, L., Dietrich, B.E., Pavan, M., Gross, S., Barmet, C., Pruessmann, K.P., 2017. Gradient and shim pre-emphasis by inversion of a linear time-invariant system model. Magn Reson Med 78, 1607–1622. [Link](https://doi.org/10.1002/mrm.26531)