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paper.md

@@ -274,7 +274,7 @@ Researchers followed the inversion recovery T<sub>1</sub> mapping protocol optim
 Data submissions for the challenge were handled through a GitHub repository ([https://github.com/rrsg2020/data_submission](https://github.com/rrsg2020/data_submission)), enabling a standardized and transparent process. All datasets were converted to the NIfTI format, and images for all TIs were concatenated into a single NIfTI file. Each submission included a YAML file to store additional information (submitter details, acquisition details, and phantom or human subject details). Submissions were reviewed [^submission-review], and following acceptance the datasets were uploaded to OSF.io ([osf.io/ywc9g/](http://www.osf.io/ywc9g/)). A Jupyter Notebook [@Kluyver2016-nl;@Beg2021-ps] pipeline using qMRLab [@Karakuzu2020-ul;@Cabana2015-zg] was used to process the T<sub>1</sub> maps and to conduct quality-control checks. MyBinder links to Jupyter notebooks that reproduced each T<sub>1</sub> map were shared in each respective submission GitHub issue to easily reproduce the results in web browsers while maintaining consistent computational environments. Eighteen submissions were included in the analysis, which resulted in 39 T<sub>1</sub> maps of the NIST/system phantom, and 56 brain T<sub>1</sub> maps. Figure 1 illustrates all the submissions that acquired phantom data (Figure 1-a) and human data (Figure 1-b), the MRI scanner vendors, and the resulting T<sub>1</sub> mapping datasets. Some submissions included measurements where both complex and magnitude-only data from the same acquisition were used to fit T<sub>1</sub> maps, thus the total number of unique acquisitions is lower than the numbers reported above (27 for phantom data and 44 for human data). The datasets were collected on systems from three MRI manufacturers (Siemens, GE, Philips) and were acquired at 3T [^three-t], except for one dataset acquired at 0.35T (the ViewRay MRidian MR-linac).
 
 <p class="caption">
-<b>Figure 1</b>. List of the datasets submitted to the challenge. Submissions that included phantom data are shown in a), and those that included human brain data are shown in b). For the phantom (panel a), each submission acquired its data using a single phantom, however, some researchers shared the same physical phantom with each other. Green indicates submissions used for inter-submission analyses, and orange indicates the sites used for intra-submission analyses. T<sub>1</sub> maps used in the calculations of inter- (green) and intra- (orange) submission coefficients of variation (COV) are indicated with asterisks. Images c) and d) illustrate the ROI choice in phantom and humans.
+<b>Figure 1</b> A snapshot of the figures (top row) included in the reproducible preprint (https://preprint.neurolibre.org/10.55458/neurolibre.00023) and the dashboard (bottom row, https://rrsg2020.db.neurolibre.org).
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