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 5 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 fifth&nbsp;part of 14 parts of the full dataset (5/14). 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) = 30ms. 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 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>