Beware (Surprisingly Common) Left-Right Flips in Your MRI Data: An Efficient and Robust Method to Check MRI Dataset Consistency Using AFNI Article Swipe
Daniel Glen
,
Paul A. Taylor
,
Bradley R. Buchsbaum
,
Robert W. Cox
,
Richard C. Reynolds
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3389/fninf.2020.00018
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3389/fninf.2020.00018
Knowing the difference between left and right is generally assumed throughout the brain MRI research community. However, we note widespread occurrences of left-right orientation errors in MRI open database repositories where volumes have contained systematic left-right flips between subject EPIs and anatomicals, due to having incorrect or missing file header information. Here we present a simple method in AFNI for determining the consistency of left and right within a pair of acquired volumes for a particular subject; the presence of EPI-anatomical inconsistency, for example, is a sign that dataset header information likely requires correction. The method contains both a quantitative evaluation as well as a visualizable verification. We test the functionality using publicly available datasets. Left-right flipping is not immediately obvious in most cases, so we also present visualization methods for looking at this problem (and other potential problems), using examples from both FMRI and DTI datasets.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fninf.2020.00018
- OA Status
- gold
- Cited By
- 27
- References
- 15
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3028343163
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3028343163Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3389/fninf.2020.00018Digital Object Identifier
- Title
-
Beware (Surprisingly Common) Left-Right Flips in Your MRI Data: An Efficient and Robust Method to Check MRI Dataset Consistency Using AFNIWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-05-25Full publication date if available
- Authors
-
Daniel Glen, Paul A. Taylor, Bradley R. Buchsbaum, Robert W. Cox, Richard C. ReynoldsList of authors in order
- Landing page
-
https://doi.org/10.3389/fninf.2020.00018Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.3389/fninf.2020.00018Direct OA link when available
- Concepts
-
Header, Consistency (knowledge bases), Computer science, Data mining, Artificial intelligence, Orientation (vector space), Left and right, Pattern recognition (psychology), Mathematics, Engineering, Structural engineering, Computer network, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
27Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 8, 2023: 11, 2022: 2, 2021: 2Per-year citation counts (last 5 years)
- References (count)
-
15Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3028343163 |
|---|---|
| doi | https://doi.org/10.3389/fninf.2020.00018 |
| ids.doi | https://doi.org/10.3389/fninf.2020.00018 |
| ids.mag | 3028343163 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/32528270 |
| ids.openalex | https://openalex.org/W3028343163 |
| fwci | 2.133945 |
| type | article |
| title | Beware (Surprisingly Common) Left-Right Flips in Your MRI Data: An Efficient and Robust Method to Check MRI Dataset Consistency Using AFNI |
| biblio.issue | |
| biblio.volume | 14 |
| biblio.last_page | 18 |
| biblio.first_page | 18 |
| topics[0].id | https://openalex.org/T10241 |
| topics[0].field.id | https://openalex.org/fields/28 |
| topics[0].field.display_name | Neuroscience |
| topics[0].score | 0.9995999932289124 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2805 |
| topics[0].subfield.display_name | Cognitive Neuroscience |
| topics[0].display_name | Functional Brain Connectivity Studies |
| topics[1].id | https://openalex.org/T11304 |
| topics[1].field.id | https://openalex.org/fields/27 |
| topics[1].field.display_name | Medicine |
| topics[1].score | 0.991599977016449 |
| topics[1].domain.id | https://openalex.org/domains/4 |
| topics[1].domain.display_name | Health Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2741 |
| topics[1].subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| topics[1].display_name | Advanced Neuroimaging Techniques and Applications |
| topics[2].id | https://openalex.org/T10378 |
| topics[2].field.id | https://openalex.org/fields/27 |
| topics[2].field.display_name | Medicine |
| topics[2].score | 0.9853000044822693 |
| topics[2].domain.id | https://openalex.org/domains/4 |
| topics[2].domain.display_name | Health Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2741 |
| topics[2].subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| topics[2].display_name | Advanced MRI Techniques and Applications |
| funders[0].id | https://openalex.org/F4320332161 |
| funders[0].ror | https://ror.org/01cwqze88 |
| funders[0].display_name | National Institutes of Health |
| funders[1].id | https://openalex.org/F4320337346 |
| funders[1].ror | https://ror.org/04xeg9z08 |
| funders[1].display_name | National Institute of Mental Health |
| is_xpac | False |
| apc_list.value | 2950 |
| apc_list.currency | USD |
| apc_list.value_usd | 2950 |
| apc_paid.value | 2950 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 2950 |
| concepts[0].id | https://openalex.org/C48105269 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8579040765762329 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1141160 |
| concepts[0].display_name | Header |
| concepts[1].id | https://openalex.org/C2776436953 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7158370018005371 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q5163215 |
| concepts[1].display_name | Consistency (knowledge bases) |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.6785846948623657 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C124101348 |
| concepts[3].level | 1 |
| concepts[3].score | 0.47789227962493896 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[3].display_name | Data mining |
| concepts[4].id | https://openalex.org/C154945302 |
| concepts[4].level | 1 |
| concepts[4].score | 0.459425687789917 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[4].display_name | Artificial intelligence |
| concepts[5].id | https://openalex.org/C16345878 |
| concepts[5].level | 2 |
| concepts[5].score | 0.41534504294395447 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q107472979 |
| concepts[5].display_name | Orientation (vector space) |
| concepts[6].id | https://openalex.org/C2776719672 |
| concepts[6].level | 2 |
| concepts[6].score | 0.4117034673690796 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q17098435 |
| concepts[6].display_name | Left and right |
| concepts[7].id | https://openalex.org/C153180895 |
| concepts[7].level | 2 |
| concepts[7].score | 0.3723219931125641 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q7148389 |
| concepts[7].display_name | Pattern recognition (psychology) |
| concepts[8].id | https://openalex.org/C33923547 |
| concepts[8].level | 0 |
| concepts[8].score | 0.140752911567688 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[8].display_name | Mathematics |
| concepts[9].id | https://openalex.org/C127413603 |
| concepts[9].level | 0 |
| concepts[9].score | 0.0 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[9].display_name | Engineering |
| concepts[10].id | https://openalex.org/C66938386 |
| concepts[10].level | 1 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q633538 |
| concepts[10].display_name | Structural engineering |
| concepts[11].id | https://openalex.org/C31258907 |
| concepts[11].level | 1 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q1301371 |
| concepts[11].display_name | Computer network |
| concepts[12].id | https://openalex.org/C2524010 |
| concepts[12].level | 1 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q8087 |
| concepts[12].display_name | Geometry |
| keywords[0].id | https://openalex.org/keywords/header |
| keywords[0].score | 0.8579040765762329 |
| keywords[0].display_name | Header |
| keywords[1].id | https://openalex.org/keywords/consistency |
| keywords[1].score | 0.7158370018005371 |
| keywords[1].display_name | Consistency (knowledge bases) |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.6785846948623657 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/data-mining |
| keywords[3].score | 0.47789227962493896 |
| keywords[3].display_name | Data mining |
| keywords[4].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[4].score | 0.459425687789917 |
| keywords[4].display_name | Artificial intelligence |
| keywords[5].id | https://openalex.org/keywords/orientation |
| keywords[5].score | 0.41534504294395447 |
| keywords[5].display_name | Orientation (vector space) |
| keywords[6].id | https://openalex.org/keywords/left-and-right |
| keywords[6].score | 0.4117034673690796 |
| keywords[6].display_name | Left and right |
| keywords[7].id | https://openalex.org/keywords/pattern-recognition |
| keywords[7].score | 0.3723219931125641 |
| keywords[7].display_name | Pattern recognition (psychology) |
| keywords[8].id | https://openalex.org/keywords/mathematics |
| keywords[8].score | 0.140752911567688 |
| keywords[8].display_name | Mathematics |
| language | en |
| locations[0].id | doi:10.3389/fninf.2020.00018 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S179816892 |
| locations[0].source.issn | 1662-5196 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1662-5196 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Frontiers in Neuroinformatics |
| locations[0].source.host_organization | https://openalex.org/P4310320527 |
| locations[0].source.host_organization_name | Frontiers Media |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320527 |
| locations[0].source.host_organization_lineage_names | Frontiers Media |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Frontiers in Neuroinformatics |
| locations[0].landing_page_url | https://doi.org/10.3389/fninf.2020.00018 |
| locations[1].id | pmid:32528270 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | Frontiers in neuroinformatics |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/32528270 |
| locations[2].id | pmh:oai:doaj.org/article:e85b11cbf16940fdb52e60dcd3d07831 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S4306401280 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | cc-by-sa |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | https://openalex.org/licenses/cc-by-sa |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Frontiers in Neuroinformatics, Vol 14 (2020) |
| locations[2].landing_page_url | https://doaj.org/article/e85b11cbf16940fdb52e60dcd3d07831 |
| locations[3].id | pmh:oai:pubmedcentral.nih.gov:7263312 |
| locations[3].is_oa | True |
| locations[3].source.id | https://openalex.org/S2764455111 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | False |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | PubMed Central |
| locations[3].source.host_organization | https://openalex.org/I1299303238 |
| locations[3].source.host_organization_name | National Institutes of Health |
| locations[3].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[3].license | cc-by |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | Text |
| locations[3].license_id | https://openalex.org/licenses/cc-by |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | Front Neuroinform |
| locations[3].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/7263312 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5048446779 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-8456-5647 |
| authorships[0].author.display_name | Daniel Glen |
| authorships[0].affiliations[0].raw_affiliation_string | Scientific and Statistical Computing Core, NIMH/NIH/DHHS, Bethesda, MD, United States |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Daniel R. Glen |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Scientific and Statistical Computing Core, NIMH/NIH/DHHS, Bethesda, MD, United States |
| authorships[1].author.id | https://openalex.org/A5005787322 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-0488-6796 |
| authorships[1].author.display_name | Paul A. Taylor |
| authorships[1].affiliations[0].raw_affiliation_string | Scientific and Statistical Computing Core, NIMH/NIH/DHHS, Bethesda, MD, United States |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Paul A. Taylor |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Scientific and Statistical Computing Core, NIMH/NIH/DHHS, Bethesda, MD, United States |
| authorships[2].author.id | https://openalex.org/A5055504859 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-1108-4866 |
| authorships[2].author.display_name | Bradley R. Buchsbaum |
| authorships[2].countries | CA |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I185261750 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Psychology, University of Toronto, Toronto, ON, Canada |
| authorships[2].affiliations[1].institution_ids | https://openalex.org/I2802437833 |
| authorships[2].affiliations[1].raw_affiliation_string | Rotman Research Institute at Baycrest, Toronto, ON, Canada |
| authorships[2].institutions[0].id | https://openalex.org/I2802437833 |
| authorships[2].institutions[0].ror | https://ror.org/03gp5b411 |
| authorships[2].institutions[0].type | healthcare |
| authorships[2].institutions[0].lineage | https://openalex.org/I2802437833 |
| authorships[2].institutions[0].country_code | CA |
| authorships[2].institutions[0].display_name | Baycrest Hospital |
| authorships[2].institutions[1].id | https://openalex.org/I185261750 |
| authorships[2].institutions[1].ror | https://ror.org/03dbr7087 |
| authorships[2].institutions[1].type | education |
| authorships[2].institutions[1].lineage | https://openalex.org/I185261750 |
| authorships[2].institutions[1].country_code | CA |
| authorships[2].institutions[1].display_name | University of Toronto |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Bradley R. Buchsbaum |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Psychology, University of Toronto, Toronto, ON, Canada, Rotman Research Institute at Baycrest, Toronto, ON, Canada |
| authorships[3].author.id | https://openalex.org/A5062395162 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-0031-1568 |
| authorships[3].author.display_name | Robert W. Cox |
| authorships[3].affiliations[0].raw_affiliation_string | Scientific and Statistical Computing Core, NIMH/NIH/DHHS, Bethesda, MD, United States |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Robert W. Cox |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Scientific and Statistical Computing Core, NIMH/NIH/DHHS, Bethesda, MD, United States |
| authorships[4].author.id | https://openalex.org/A5025001284 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-7267-5563 |
| authorships[4].author.display_name | Richard C. Reynolds |
| authorships[4].affiliations[0].raw_affiliation_string | Scientific and Statistical Computing Core, NIMH/NIH/DHHS, Bethesda, MD, United States |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Richard C. Reynolds |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Scientific and Statistical Computing Core, NIMH/NIH/DHHS, Bethesda, MD, United States |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.3389/fninf.2020.00018 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Beware (Surprisingly Common) Left-Right Flips in Your MRI Data: An Efficient and Robust Method to Check MRI Dataset Consistency Using AFNI |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10241 |
| primary_topic.field.id | https://openalex.org/fields/28 |
| primary_topic.field.display_name | Neuroscience |
| primary_topic.score | 0.9995999932289124 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2805 |
| primary_topic.subfield.display_name | Cognitive Neuroscience |
| primary_topic.display_name | Functional Brain Connectivity Studies |
| related_works | https://openalex.org/W2171597999, https://openalex.org/W2189136227, https://openalex.org/W1866537546, https://openalex.org/W630850086, https://openalex.org/W3200508093, https://openalex.org/W4372053344, https://openalex.org/W3193978431, https://openalex.org/W2379752180, https://openalex.org/W2519240373, https://openalex.org/W1496096987 |
| cited_by_count | 27 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 2 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 8 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 11 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 2 |
| counts_by_year[4].year | 2021 |
| counts_by_year[4].cited_by_count | 2 |
| counts_by_year[5].year | 2020 |
| counts_by_year[5].cited_by_count | 2 |
| locations_count | 4 |
| best_oa_location.id | doi:10.3389/fninf.2020.00018 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S179816892 |
| best_oa_location.source.issn | 1662-5196 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1662-5196 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Frontiers in Neuroinformatics |
| best_oa_location.source.host_organization | https://openalex.org/P4310320527 |
| best_oa_location.source.host_organization_name | Frontiers Media |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320527 |
| best_oa_location.source.host_organization_lineage_names | Frontiers Media |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Frontiers in Neuroinformatics |
| best_oa_location.landing_page_url | https://doi.org/10.3389/fninf.2020.00018 |
| primary_location.id | doi:10.3389/fninf.2020.00018 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S179816892 |
| primary_location.source.issn | 1662-5196 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1662-5196 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Frontiers in Neuroinformatics |
| primary_location.source.host_organization | https://openalex.org/P4310320527 |
| primary_location.source.host_organization_name | Frontiers Media |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320527 |
| primary_location.source.host_organization_lineage_names | Frontiers Media |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Frontiers in Neuroinformatics |
| primary_location.landing_page_url | https://doi.org/10.3389/fninf.2020.00018 |
| publication_date | 2020-05-25 |
| publication_year | 2020 |
| referenced_works | https://openalex.org/W1977821888, https://openalex.org/W2008607322, https://openalex.org/W2117140276, https://openalex.org/W2162576262, https://openalex.org/W2167868121, https://openalex.org/W2888467429, https://openalex.org/W2025009638, https://openalex.org/W2015772604, https://openalex.org/W2951103577, https://openalex.org/W1968557458, https://openalex.org/W2775442832, https://openalex.org/W2145680887, https://openalex.org/W2018731294, https://openalex.org/W2112674546, https://openalex.org/W2033713584 |
| referenced_works_count | 15 |
| abstract_inverted_index.a | 54, 68, 74, 85, 98, 104 |
| abstract_inverted_index.We | 107 |
| abstract_inverted_index.as | 101, 103 |
| abstract_inverted_index.at | 132 |
| abstract_inverted_index.in | 25, 57, 121 |
| abstract_inverted_index.is | 7, 84, 117 |
| abstract_inverted_index.of | 21, 63, 70, 79 |
| abstract_inverted_index.or | 46 |
| abstract_inverted_index.so | 124 |
| abstract_inverted_index.to | 43 |
| abstract_inverted_index.we | 17, 52, 125 |
| abstract_inverted_index.DTI | 145 |
| abstract_inverted_index.MRI | 13, 26 |
| abstract_inverted_index.The | 94 |
| abstract_inverted_index.and | 5, 40, 65, 144 |
| abstract_inverted_index.due | 42 |
| abstract_inverted_index.for | 59, 73, 82, 130 |
| abstract_inverted_index.not | 118 |
| abstract_inverted_index.the | 1, 11, 61, 77, 109 |
| abstract_inverted_index.(and | 135 |
| abstract_inverted_index.AFNI | 58 |
| abstract_inverted_index.EPIs | 39 |
| abstract_inverted_index.FMRI | 143 |
| abstract_inverted_index.Here | 51 |
| abstract_inverted_index.also | 126 |
| abstract_inverted_index.both | 97, 142 |
| abstract_inverted_index.file | 48 |
| abstract_inverted_index.from | 141 |
| abstract_inverted_index.have | 32 |
| abstract_inverted_index.left | 4, 64 |
| abstract_inverted_index.most | 122 |
| abstract_inverted_index.note | 18 |
| abstract_inverted_index.open | 27 |
| abstract_inverted_index.pair | 69 |
| abstract_inverted_index.sign | 86 |
| abstract_inverted_index.test | 108 |
| abstract_inverted_index.that | 87 |
| abstract_inverted_index.this | 133 |
| abstract_inverted_index.well | 102 |
| abstract_inverted_index.brain | 12 |
| abstract_inverted_index.flips | 36 |
| abstract_inverted_index.other | 136 |
| abstract_inverted_index.right | 6, 66 |
| abstract_inverted_index.using | 111, 139 |
| abstract_inverted_index.where | 30 |
| abstract_inverted_index.cases, | 123 |
| abstract_inverted_index.errors | 24 |
| abstract_inverted_index.having | 44 |
| abstract_inverted_index.header | 49, 89 |
| abstract_inverted_index.likely | 91 |
| abstract_inverted_index.method | 56, 95 |
| abstract_inverted_index.simple | 55 |
| abstract_inverted_index.within | 67 |
| abstract_inverted_index.Knowing | 0 |
| abstract_inverted_index.assumed | 9 |
| abstract_inverted_index.between | 3, 37 |
| abstract_inverted_index.dataset | 88 |
| abstract_inverted_index.looking | 131 |
| abstract_inverted_index.methods | 129 |
| abstract_inverted_index.missing | 47 |
| abstract_inverted_index.obvious | 120 |
| abstract_inverted_index.present | 53, 127 |
| abstract_inverted_index.problem | 134 |
| abstract_inverted_index.subject | 38 |
| abstract_inverted_index.volumes | 31, 72 |
| abstract_inverted_index.However, | 16 |
| abstract_inverted_index.acquired | 71 |
| abstract_inverted_index.contains | 96 |
| abstract_inverted_index.database | 28 |
| abstract_inverted_index.example, | 83 |
| abstract_inverted_index.examples | 140 |
| abstract_inverted_index.flipping | 116 |
| abstract_inverted_index.presence | 78 |
| abstract_inverted_index.publicly | 112 |
| abstract_inverted_index.requires | 92 |
| abstract_inverted_index.research | 14 |
| abstract_inverted_index.subject; | 76 |
| abstract_inverted_index.available | 113 |
| abstract_inverted_index.contained | 33 |
| abstract_inverted_index.datasets. | 114, 146 |
| abstract_inverted_index.generally | 8 |
| abstract_inverted_index.incorrect | 45 |
| abstract_inverted_index.potential | 137 |
| abstract_inverted_index.Left-right | 115 |
| abstract_inverted_index.community. | 15 |
| abstract_inverted_index.difference | 2 |
| abstract_inverted_index.evaluation | 100 |
| abstract_inverted_index.left-right | 22, 35 |
| abstract_inverted_index.particular | 75 |
| abstract_inverted_index.problems), | 138 |
| abstract_inverted_index.systematic | 34 |
| abstract_inverted_index.throughout | 10 |
| abstract_inverted_index.widespread | 19 |
| abstract_inverted_index.consistency | 62 |
| abstract_inverted_index.correction. | 93 |
| abstract_inverted_index.determining | 60 |
| abstract_inverted_index.immediately | 119 |
| abstract_inverted_index.information | 90 |
| abstract_inverted_index.occurrences | 20 |
| abstract_inverted_index.orientation | 23 |
| abstract_inverted_index.anatomicals, | 41 |
| abstract_inverted_index.information. | 50 |
| abstract_inverted_index.quantitative | 99 |
| abstract_inverted_index.repositories | 29 |
| abstract_inverted_index.visualizable | 105 |
| abstract_inverted_index.functionality | 110 |
| abstract_inverted_index.verification. | 106 |
| abstract_inverted_index.visualization | 128 |
| abstract_inverted_index.EPI-anatomical | 80 |
| abstract_inverted_index.inconsistency, | 81 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 93 |
| corresponding_author_ids | https://openalex.org/A5048446779 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile.value | 0.86486685 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |