cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7393173
title: 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 7 of 14

description: This dataset is part of the work https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full. This is the seventh part of 14 parts of the full dataset (7/14). 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 repetition time (TR) = 300ms, 400ms, 500ms, and echo time (TE) = 40ms. Under <strong>each</strong> simulated scanning sequence, there are 500 brain volumes. The segmentation labels for each tissue are contained in the first part which you may find at https://zenodo.org/record/7294916 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 https://brainweb.bic.mni.mcgill.ca/cgi/bw/submit_request. 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 https://www.humanconnectome.org/study/hcp-young-adult and randomly select 500 brains as anatomical references. Other details of this dataset can be found at https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full where the details of the data construction are discussed. All parts of the whole dataset can be found at: Part 1: https://zenodo.org/record/7294916 Part 2: https://zenodo.org/record/7389550 Part 3: https://zenodo.org/record/7390382 Part 4: https://zenodo.org/record/7390741 Part 5: https://zenodo.org/record/7391205 Part 6: https://zenodo.org/record/7393060 Part 7: https://zenodo.org/record/7393174 Part 8: https://zenodo.org/record/7393347 Part 9: https://zenodo.org/record/7394250 Part 10: https://zenodo.org/record/7394667 Part 11: https://zenodo.org/record/7394939 Part 12: https://zenodo.org/record/7395031 Part 13: https://zenodo.org/record/7395620 Part 14: https://zenodo.org/record/7395622
DOI: 10.5281/zenodo.7393347
title: 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 8 of 14

description: This dataset is part of the work https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full. This is the eighth part of 14 parts of the full dataset (8/14). 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 repetition time (TR) = 600ms, 700ms, 800ms, and echo time (TE) = 10ms. Under <strong>each</strong> simulated scanning sequence, there are 500 brain volumes. The segmentation labels for each tissue are contained in the first part which you may find at https://zenodo.org/record/7294916 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 https://brainweb.bic.mni.mcgill.ca/cgi/bw/submit_request. 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 https://www.humanconnectome.org/study/hcp-young-adult and randomly select 500 brains as anatomical references. Other details of this dataset can be found at https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full where the details of the data construction are discussed. All parts of the whole dataset can be found at: Part 1: https://zenodo.org/record/7294916 Part 2: https://zenodo.org/record/7389550 Part 3: https://zenodo.org/record/7390382 Part 4: https://zenodo.org/record/7390741 Part 5: https://zenodo.org/record/7391205 Part 6: https://zenodo.org/record/7393060 Part 7: https://zenodo.org/record/7393174 Part 8: https://zenodo.org/record/7393347 Part 9: https://zenodo.org/record/7394250 Part 10: https://zenodo.org/record/7394667 Part 11: https://zenodo.org/record/7394939 Part 12: https://zenodo.org/record/7395031 Part 13: https://zenodo.org/record/7395620 Part 14: https://zenodo.org/record/7395622
DOI: 10.5281/zenodo.7393346
title: 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 8 of 14

description: This dataset is part of the work https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full. This is the eighth part of 14 parts of the full dataset (8/14). 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 repetition time (TR) = 600ms, 700ms, 800ms, and echo time (TE) = 10ms. Under <strong>each</strong> simulated scanning sequence, there are 500 brain volumes. The segmentation labels for each tissue are contained in the first part which you may find at https://zenodo.org/record/7294916 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 https://brainweb.bic.mni.mcgill.ca/cgi/bw/submit_request. 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 https://www.humanconnectome.org/study/hcp-young-adult and randomly select 500 brains as anatomical references. Other details of this dataset can be found at https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full where the details of the data construction are discussed. All parts of the whole dataset can be found at: Part 1: https://zenodo.org/record/7294916 Part 2: https://zenodo.org/record/7389550 Part 3: https://zenodo.org/record/7390382 Part 4: https://zenodo.org/record/7390741 Part 5: https://zenodo.org/record/7391205 Part 6: https://zenodo.org/record/7393060 Part 7: https://zenodo.org/record/7393174 Part 8: https://zenodo.org/record/7393347 Part 9: https://zenodo.org/record/7394250 Part 10: https://zenodo.org/record/7394667 Part 11: https://zenodo.org/record/7394939 Part 12: https://zenodo.org/record/7395031 Part 13: https://zenodo.org/record/7395620 Part 14: https://zenodo.org/record/7395622
DOI: 10.5281/zenodo.7394250
title: 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 9 of 14

description: This dataset is part of the work https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full. This is the ninth part of 14 parts of the full dataset (9/14). 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 repetition time (TR) = 600ms, 700ms, 800ms, and echo time (TE) = 15ms. Under <strong>each</strong> simulated scanning sequence, there are 500 brain volumes. The segmentation labels for each tissue are contained in the first part which you may find at https://zenodo.org/record/7294916 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 https://brainweb.bic.mni.mcgill.ca/cgi/bw/submit_request. 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 https://www.humanconnectome.org/study/hcp-young-adult and randomly select 500 brains as anatomical references. Other details of this dataset can be found at https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full where the details of the data construction are discussed. All parts of the whole dataset can be found at: Part 1: https://zenodo.org/record/7294916 Part 2: https://zenodo.org/record/7389550 Part 3: https://zenodo.org/record/7390382 Part 4: https://zenodo.org/record/7390741 Part 5: https://zenodo.org/record/7391205 Part 6: https://zenodo.org/record/7393060 Part 7: https://zenodo.org/record/7393174 Part 8: https://zenodo.org/record/7393347 Part 9: https://zenodo.org/record/7394250 Part 10: https://zenodo.org/record/7394667 Part 11: https://zenodo.org/record/7394939 Part 12: https://zenodo.org/record/7395031 Part 13: https://zenodo.org/record/7395620 Part 14: https://zenodo.org/record/7395622
DOI: 10.5281/zenodo.7394249
title: 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 9 of 14

description: This dataset is part of the work https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full. This is the ninth part of 14 parts of the full dataset (9/14). 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 repetition time (TR) = 600ms, 700ms, 800ms, and echo time (TE) = 15ms. Under <strong>each</strong> simulated scanning sequence, there are 500 brain volumes. The segmentation labels for each tissue are contained in the first part which you may find at https://zenodo.org/record/7294916 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 https://brainweb.bic.mni.mcgill.ca/cgi/bw/submit_request. 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 https://www.humanconnectome.org/study/hcp-young-adult and randomly select 500 brains as anatomical references. Other details of this dataset can be found at https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full where the details of the data construction are discussed. All parts of the whole dataset can be found at: Part 1: https://zenodo.org/record/7294916 Part 2: https://zenodo.org/record/7389550 Part 3: https://zenodo.org/record/7390382 Part 4: https://zenodo.org/record/7390741 Part 5: https://zenodo.org/record/7391205 Part 6: https://zenodo.org/record/7393060 Part 7: https://zenodo.org/record/7393174 Part 8: https://zenodo.org/record/7393347 Part 9: https://zenodo.org/record/7394250 Part 10: https://zenodo.org/record/7394667 Part 11: https://zenodo.org/record/7394939 Part 12: https://zenodo.org/record/7395031 Part 13: https://zenodo.org/record/7395620 Part 14: https://zenodo.org/record/7395622
DOI: 10.5281/zenodo.7394667
title: 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 10 of 14

description: This dataset is part of the work https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full. This is the tenth part of 14 parts of the full dataset (10/14). 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 repetition time (TR) = 600ms, 700ms, 800ms, and echo time (TE) = 20ms. Under <strong>each</strong> simulated scanning sequence, there are 500 brain volumes. The segmentation labels for each tissue are contained in the first part which you may find at https://zenodo.org/record/7294916 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 https://brainweb.bic.mni.mcgill.ca/cgi/bw/submit_request. 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 https://www.humanconnectome.org/study/hcp-young-adult and randomly select 500 brains as anatomical references. Other details of this dataset can be found at https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full where the details of the data construction are discussed. All parts of the whole dataset can be found at: Part 1: https://zenodo.org/record/7294916 Part 2: https://zenodo.org/record/7389550 Part 3: https://zenodo.org/record/7390382 Part 4: https://zenodo.org/record/7390741 Part 5: https://zenodo.org/record/7391205 Part 6: https://zenodo.org/record/7393060 Part 7: https://zenodo.org/record/7393174 Part 8: https://zenodo.org/record/7393347 Part 9: https://zenodo.org/record/7394250 Part 10: https://zenodo.org/record/7394667 Part 11: https://zenodo.org/record/7394939 Part 12: https://zenodo.org/record/7395031 Part 13: https://zenodo.org/record/7395620 Part 14: https://zenodo.org/record/7395622
DOI: 10.5281/zenodo.7394666
title: 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 10 of 14

description: This dataset is part of the work https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full. This is the tenth part of 14 parts of the full dataset (10/14). 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 repetition time (TR) = 600ms, 700ms, 800ms, and echo time (TE) = 20ms. Under <strong>each</strong> simulated scanning sequence, there are 500 brain volumes. The segmentation labels for each tissue are contained in the first part which you may find at https://zenodo.org/record/7294916 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 https://brainweb.bic.mni.mcgill.ca/cgi/bw/submit_request. 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 https://www.humanconnectome.org/study/hcp-young-adult and randomly select 500 brains as anatomical references. Other details of this dataset can be found at https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full where the details of the data construction are discussed. All parts of the whole dataset can be found at: Part 1: https://zenodo.org/record/7294916 Part 2: https://zenodo.org/record/7389550 Part 3: https://zenodo.org/record/7390382 Part 4: https://zenodo.org/record/7390741 Part 5: https://zenodo.org/record/7391205 Part 6: https://zenodo.org/record/7393060 Part 7: https://zenodo.org/record/7393174 Part 8: https://zenodo.org/record/7393347 Part 9: https://zenodo.org/record/7394250 Part 10: https://zenodo.org/record/7394667 Part 11: https://zenodo.org/record/7394939 Part 12: https://zenodo.org/record/7395031 Part 13: https://zenodo.org/record/7395620 Part 14: https://zenodo.org/record/7395622
DOI: 10.5281/zenodo.7394939
title: 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 11 of 14

description: This dataset is part of the work https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full. This is the eleventh part of 14 parts of the full dataset (11/14). 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 repetition time (TR) = 600ms, 700ms, 800ms, and echo time (TE) = 25ms. Under <strong>each</strong> simulated scanning sequence, there are 500 brain volumes. The segmentation labels for each tissue are contained in the first part which you may find at https://zenodo.org/record/7294916 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 https://brainweb.bic.mni.mcgill.ca/cgi/bw/submit_request. 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 https://www.humanconnectome.org/study/hcp-young-adult and randomly select 500 brains as anatomical references. Other details of this dataset can be found at https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full where the details of the data construction are discussed. All parts of the whole dataset can be found at: Part 1: https://zenodo.org/record/7294916 Part 2: https://zenodo.org/record/7389550 Part 3: https://zenodo.org/record/7390382 Part 4: https://zenodo.org/record/7390741 Part 5: https://zenodo.org/record/7391205 Part 6: https://zenodo.org/record/7393060 Part 7: https://zenodo.org/record/7393174 Part 8: https://zenodo.org/record/7393347 Part 9: https://zenodo.org/record/7394250 Part 10: https://zenodo.org/record/7394667 Part 11: https://zenodo.org/record/7394939 Part 12: https://zenodo.org/record/7395031 Part 13: https://zenodo.org/record/7395620 Part 14: https://zenodo.org/record/7395622
DOI: 10.5281/zenodo.7394938
title: 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 11 of 14

description: This dataset is part of the work https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full. This is the eleventh part of 14 parts of the full dataset (11/14). 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 repetition time (TR) = 600ms, 700ms, 800ms, and echo time (TE) = 25ms. Under <strong>each</strong> simulated scanning sequence, there are 500 brain volumes. The segmentation labels for each tissue are contained in the first part which you may find at https://zenodo.org/record/7294916 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 https://brainweb.bic.mni.mcgill.ca/cgi/bw/submit_request. 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 https://www.humanconnectome.org/study/hcp-young-adult and randomly select 500 brains as anatomical references. Other details of this dataset can be found at https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full where the details of the data construction are discussed. All parts of the whole dataset can be found at: Part 1: https://zenodo.org/record/7294916 Part 2: https://zenodo.org/record/7389550 Part 3: https://zenodo.org/record/7390382 Part 4: https://zenodo.org/record/7390741 Part 5: https://zenodo.org/record/7391205 Part 6: https://zenodo.org/record/7393060 Part 7: https://zenodo.org/record/7393174 Part 8: https://zenodo.org/record/7393347 Part 9: https://zenodo.org/record/7394250 Part 10: https://zenodo.org/record/7394667 Part 11: https://zenodo.org/record/7394939 Part 12: https://zenodo.org/record/7395031 Part 13: https://zenodo.org/record/7395620 Part 14: https://zenodo.org/record/7395622
DOI: 10.5281/zenodo.7395031
title: 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 12 of 14

description: This dataset is part of the work https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full. This is the twelfth part of 14 parts of the full dataset (12/14). 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 repetition time (TR) = 600ms, 700ms, 800ms, and echo time (TE) = 30ms. Under <strong>each</strong> simulated scanning sequence, there are 500 brain volumes. The segmentation labels for each tissue are contained in the first part which you may find at https://zenodo.org/record/7294916 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 https://brainweb.bic.mni.mcgill.ca/cgi/bw/submit_request. 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 https://www.humanconnectome.org/study/hcp-young-adult and randomly select 500 brains as anatomical references. Other details of this dataset can be found at https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full where the details of the data construction are discussed. All parts of the whole dataset can be found at: Part 1: https://zenodo.org/record/7294916 Part 2: https://zenodo.org/record/7389550 Part 3: https://zenodo.org/record/7390382 Part 4: https://zenodo.org/record/7390741 Part 5: https://zenodo.org/record/7391205 Part 6: https://zenodo.org/record/7393060 Part 7: https://zenodo.org/record/7393174 Part 8: https://zenodo.org/record/7393347 Part 9: https://zenodo.org/record/7394250 Part 10: https://zenodo.org/record/7394667 Part 11: https://zenodo.org/record/7394939 Part 12: https://zenodo.org/record/7395031 Part 13: https://zenodo.org/record/7395620 Part 14: https://zenodo.org/record/7395622