Datasets of "Influence of contrast and texture based image modifications on the performance and attention shift of U-Net models for brain tissue segmentation" Part 2 of 14

<p>This dataset is part of the work&nbsp;<a href="https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full">https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full</a>. This is the second part of 14 parts of the full dataset (2/14). It contains 3 sets of simulated T1 weighted brain volumes in 3 simulated scanning sequences of spin-echo. The parameters of simulated scanning sequences are respectively&nbsp;repetition time (TR) =&nbsp;300ms, 400ms,&nbsp; 500ms, and echo time (TE) = 15ms. Under <strong>each</strong> simulated scanning sequence, there are 500 brain volumes.</p> <p>The segmentation labels for each tissue are contained in the first part which you may find at&nbsp;<a href="https://zenodo.org/record/7294916">https://zenodo.org/record/7294916</a></p> <p>The simulation process of this dataset involves two processes. The first is to simulate one brain under different simulated scanning sequences. For this, we use BrainWeb&nbsp;<a href="https://brainweb.bic.mni.mcgill.ca/cgi/bw/submit_request">https://brainweb.bic.mni.mcgill.ca/cgi/bw/submit_request</a>. In the custom setting, we use spin-echo and apply image artifact the same as the default setting of this page. The second process is to transform each&nbsp; simulated brain from BrainWeb to different anatomical shapes. We use Human Connectome Project (HCP) 1200 subject data&nbsp;<a href="https://www.humanconnectome.org/study/hcp-young-adult">https://www.humanconnectome.org/study/hcp-young-adult</a>&nbsp;and randomly select 500 brains as anatomical references.</p> <p>Other details of this dataset can be found at&nbsp;<a href="https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full">https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full</a>&nbsp;where the details of the data construction are discussed.</p> <p>All&nbsp;parts of the whole dataset can be found at:</p> <p>Part 1:&nbsp;<a href="https://zenodo.org/record/7294916">https://zenodo.org/record/7294916</a></p> <p>Part 2:&nbsp;<a href="https://zenodo.org/record/7389550">https://zenodo.org/record/7389550</a></p> <p>Part 3:&nbsp;<a href="https://zenodo.org/record/7390382">https://zenodo.org/record/7390382</a></p> <p>Part 4:&nbsp;<a href="https://zenodo.org/record/7390741">https://zenodo.org/record/7390741</a></p> <p>Part 5:&nbsp;<a href="https://zenodo.org/record/7391205">https://zenodo.org/record/7391205</a></p> <p>Part 6:&nbsp;<a href="https://zenodo.org/record/7393060">https://zenodo.org/record/7393060</a></p> <p>Part 7:&nbsp;<a href="https://zenodo.org/record/7393174">https://zenodo.org/record/7393174</a></p> <p>Part 8:&nbsp;<a href="https://zenodo.org/record/7393347">https://zenodo.org/record/7393347</a></p> <p>Part 9:&nbsp;<a href="https://zenodo.org/record/7394250">https://zenodo.org/record/7394250</a></p> <p>Part 10:&nbsp;<a href="https://zenodo.org/record/7394667">https://zenodo.org/record/7394667</a></p> <p>Part 11:&nbsp;<a href="https://zenodo.org/record/7394939">https://zenodo.org/record/7394939</a></p> <p>Part 12:&nbsp;<a href="https://zenodo.org/record/7395031">https://zenodo.org/record/7395031</a></p> <p>Part 13:&nbsp;<a href="https://zenodo.org/record/7395620">https://zenodo.org/record/7395620</a></p> <p>Part 14:&nbsp;<a href="https://zenodo.org/record/7395622">https://zenodo.org/record/7395622</a></p> <p>&nbsp;</p>