Magnetic resonance imaging datasets with anatomical fiducials for quality control and registration
Abstract Tools available for reproducible, quantitative assessment of brain correspondence have been limited. We previously validated the anatomical fiducial (AFID) placement protocol for point-based assessment of image registration with millimetric (mm) accuracy. In this data descriptor, we release...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-07-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-023-02330-9 |
| _version_ | 1827900051305791488 |
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| author | Alaa Taha Greydon Gilmore Mohamad Abbass Jason Kai Tristan Kuehn John Demarco Geetika Gupta Chris Zajner Daniel Cao Ryan Chevalier Abrar Ahmed Ali Hadi Bradley G. Karat Olivia W. Stanley Patrick J. Park Kayla M. Ferko Dimuthu Hemachandra Reid Vassallo Magdalena Jach Arun Thurairajah Sandy Wong Mauricio C. Tenorio Feyi Ogunsanya Ali R. Khan Jonathan C. Lau |
| author_facet | Alaa Taha Greydon Gilmore Mohamad Abbass Jason Kai Tristan Kuehn John Demarco Geetika Gupta Chris Zajner Daniel Cao Ryan Chevalier Abrar Ahmed Ali Hadi Bradley G. Karat Olivia W. Stanley Patrick J. Park Kayla M. Ferko Dimuthu Hemachandra Reid Vassallo Magdalena Jach Arun Thurairajah Sandy Wong Mauricio C. Tenorio Feyi Ogunsanya Ali R. Khan Jonathan C. Lau |
| author_sort | Alaa Taha |
| collection | DOAJ |
| description | Abstract Tools available for reproducible, quantitative assessment of brain correspondence have been limited. We previously validated the anatomical fiducial (AFID) placement protocol for point-based assessment of image registration with millimetric (mm) accuracy. In this data descriptor, we release curated AFID placements for some of the most commonly used structural magnetic resonance imaging datasets and templates. The release of our accurate placements allows for rapid quality control of image registration, teaching neuroanatomy, and clinical applications such as disease diagnosis and surgical targeting. We release placements on individual subjects from four datasets (N = 132 subjects for a total of 15,232 fiducials) and 14 brain templates (4,288 fiducials), totalling more than 300 human rater hours of annotation. We also validate human rater accuracy of released placements to be within 1 – 2 mm (using more than 45,000 Euclidean distances), consistent with prior studies. Our data is compliant with the Brain Imaging Data Structure allowing for facile incorporation into neuroimaging analysis pipelines. |
| first_indexed | 2024-03-12T23:25:46Z |
| format | Article |
| id | doaj.art-01357b737d88409ebb9f571144ab0350 |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-03-12T23:25:46Z |
| publishDate | 2023-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-01357b737d88409ebb9f571144ab03502023-07-16T11:09:08ZengNature PortfolioScientific Data2052-44632023-07-0110111110.1038/s41597-023-02330-9Magnetic resonance imaging datasets with anatomical fiducials for quality control and registrationAlaa Taha0Greydon Gilmore1Mohamad Abbass2Jason Kai3Tristan Kuehn4John Demarco5Geetika Gupta6Chris Zajner7Daniel Cao8Ryan Chevalier9Abrar Ahmed10Ali Hadi11Bradley G. Karat12Olivia W. Stanley13Patrick J. Park14Kayla M. Ferko15Dimuthu Hemachandra16Reid Vassallo17Magdalena Jach18Arun Thurairajah19Sandy Wong20Mauricio C. Tenorio21Feyi Ogunsanya22Ali R. Khan23Jonathan C. Lau24Imaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityDepartment of Clinical Neurological Sciences, Division of Neurosurgery, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversitySchool of Biomedical Engineering, Faculty of Applied Science and Faculty of Medicine, The University of British ColumbiaDepartment of Clinical Neurological Sciences, Division of Neurosurgery, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityImaging Research Laboratories, Robarts Research Institute, Western UniversityAbstract Tools available for reproducible, quantitative assessment of brain correspondence have been limited. We previously validated the anatomical fiducial (AFID) placement protocol for point-based assessment of image registration with millimetric (mm) accuracy. In this data descriptor, we release curated AFID placements for some of the most commonly used structural magnetic resonance imaging datasets and templates. The release of our accurate placements allows for rapid quality control of image registration, teaching neuroanatomy, and clinical applications such as disease diagnosis and surgical targeting. We release placements on individual subjects from four datasets (N = 132 subjects for a total of 15,232 fiducials) and 14 brain templates (4,288 fiducials), totalling more than 300 human rater hours of annotation. We also validate human rater accuracy of released placements to be within 1 – 2 mm (using more than 45,000 Euclidean distances), consistent with prior studies. Our data is compliant with the Brain Imaging Data Structure allowing for facile incorporation into neuroimaging analysis pipelines.https://doi.org/10.1038/s41597-023-02330-9 |
| spellingShingle | Alaa Taha Greydon Gilmore Mohamad Abbass Jason Kai Tristan Kuehn John Demarco Geetika Gupta Chris Zajner Daniel Cao Ryan Chevalier Abrar Ahmed Ali Hadi Bradley G. Karat Olivia W. Stanley Patrick J. Park Kayla M. Ferko Dimuthu Hemachandra Reid Vassallo Magdalena Jach Arun Thurairajah Sandy Wong Mauricio C. Tenorio Feyi Ogunsanya Ali R. Khan Jonathan C. Lau Magnetic resonance imaging datasets with anatomical fiducials for quality control and registration Scientific Data |
| title | Magnetic resonance imaging datasets with anatomical fiducials for quality control and registration |
| title_full | Magnetic resonance imaging datasets with anatomical fiducials for quality control and registration |
| title_fullStr | Magnetic resonance imaging datasets with anatomical fiducials for quality control and registration |
| title_full_unstemmed | Magnetic resonance imaging datasets with anatomical fiducials for quality control and registration |
| title_short | Magnetic resonance imaging datasets with anatomical fiducials for quality control and registration |
| title_sort | magnetic resonance imaging datasets with anatomical fiducials for quality control and registration |
| url | https://doi.org/10.1038/s41597-023-02330-9 |
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