The DOI matches its Crossref record; 96 of the 96 references it cites were found in a registry or an index.
FreeSurfer
Open accessAbstract
FreeSurfer is a suite of tools for the analysis of neuroimaging data that provides an array of algorithms to quantify the functional, connectional and structural properties of the human brain. It has evolved from a package primarily aimed at generating surface representations of the cerebral cortex into one that automatically creates models of most macroscopically visible structures in the human brain given any reasonable T1-weighted input image. It is freely available, runs on a wide variety of hardware and software platforms, and is open source.
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“The most popularly used cortical parcellation is the Freesurfer Desikan-Killiany cortical parcellation (Desikan et al., 2006; Fischl, 2012), while many other cortical parcellation schemes have also been widely used (Destrieux et al., 2010; Shattuck et al., 2008; Tzourio-Mazoyer et al., 2002).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Fischl, 2012
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In the citing paper
“All data sets were corrected for head motion, eddy currents and susceptibility distortions and are, in general, of very high quality69–73.”
From Tractography-based connectomes are dominated by false-positive connections (2016) · cites this paper as [71]
Experimental — accuracy not yet measuredIn the citing paper
“Surface based registrations that take into account the sulcal and gyral anatomy also help mitigate these confounds, and may be the future direction of the field (Fischl, 2012; Van Essen, 2012).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Fischl, 2012
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Citations
Cites
Stochastic relaxation, gibbs distributions, and the bayesian restoration of images.
Geman, S., & Geman, D. (1984) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1984.4767596 · Cited by 17,949
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324
Self-citationCortical Surface-Based Analysis
Dale, A. M., Fischl, B., & Sereno, M. I. (1999) · NeuroImage · doi:10.1006/nimg.1998.0395 · Cited by 10,910
Self-citationFischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., et al. (2002) · Neuron · doi:10.1016/s0896-6273(02)00569-x · Cited by 8,610
Self-citationCortical Surface-Based Analysis
Fischl, B., Sereno, M. I., & Dale, A. M. (1999) · NeuroImage · doi:10.1006/nimg.1998.0396 · Cited by 6,147
Self-citationMeasuring the thickness of the human cerebral cortex from magnetic resonance images
Fischl, B. R., & Dale, A. M. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.200033797 · Cited by 5,995
Self-citationAutomatically Parcellating the Human Cerebral Cortex
Fischl, B. R. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg087 · Cited by 4,208
Self-citationAccurate and robust brain image alignment using boundary-based registration
Greve, D. N., & Fischl, B. R. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.06.060 · Cited by 3,553
Self-citationAutomatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature
Destrieux, C., Fischl, B., Dale, A., & Halgren, E. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.06.010 · Cited by 2,956
Self-citationBorders of Multiple Visual Areas in Humans Revealed by Functional Magnetic Resonance Imaging
Sereno, M. I., Dale, A. M., Reppas, J. B., Kwong, K. K., Belliveau, J. W., Brady, T. J., Rosen, B. R., & Tootell, R. B. H. (1995) · Science · doi:10.1126/science.7754376 · Cited by 2,663
Research works printed but not linked: 2
- Drury, 1997, Warping fMRI activation patterns onto the visible man atlas using fluid deformations of cortical flat maps, Neuroimage, 5
- Postelnicu, 2009, Combined volumetric and surface registration, IEEE Trans. Med. Imaging, 28, 508, 10.1109/TMI.2008.2004426 · DOI
Cited by
Sorted by citations
A multi-modal parcellation of human cerebral cortex
Glasser, M. F., Coalson, T. S., Robinson, E. C., Hacker, C. D., Harwell, J., Yacoub, E., Ugurbil, K., Andersson, J., Beckmann, C. F., Jenkinson, M., et al. (2016) · Nature · doi:10.1038/nature18933 · Cited by 5,111
Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI
Schaefer, A., Kong, R., Gordon, E. M., Laumann, T. O., Zuo, X.-N., Holmes, A. J., Eickhoff, S. B., & Yeo, B. T. T. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhx179 · Cited by 3,657
fMRIPrep: A robust preprocessing pipeline for functional MRI
Esteban, O., Markiewicz, C. J., Blair, R. W., Moodie, C. A., Isik, A. I., Erramuzpe, A., Kent, J. D., Goncalves, M., DuPre, E., Snyder, M., et al. (2019) · Nature Methods · doi:10.1038/s41592-018-0235-4 · Cited by 3,905
MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation
Tournier, J.-D., Smith, R., Raffelt, D., Tabbara, R., Dhollander, T., Pietsch, M., Christiaens, D., Jeurissen, B., Yeh, C.-H., & Connelly, A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116137 · Cited by 2,974
Situating the default-mode network along a principal gradient of macroscale cortical organization
Margulies, D. S., Ghosh, S. S., Goulas, A., Falkiewicz, M., Huntenburg, J. M., Langs, G., Bezgin, G., Eickhoff, S. B., Castellanos, F. X., Petrides, M., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1608282113 · Cited by 2,321
Metadata
- Authors
- Fischl, B.
- Affiliations
- Harvard University (US)
- Corresponding author
- Fischl, Bruce
- ORCID
- Fischl, Bruce
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2012-08
- Volume
- 62
- Issue
- 2
- Pages
- 774-781
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3685476
- OpenAlex
- W4241074797
- Semantic Scholar
- 771b3c73fbaba12f5d65db39401ee9cddb224554
- Cited by
- 9,526
- References
- 96
- Citations by year
- 2026: 1247 · 2025: 1431 · 2024: 1203 · 2023: 1051 · 2022: 998 · 2021: 912 · 2020: 688 · 2019: 512 · 2018: 491 · 2017: 332 · 2016: 255 · 2015: 188 · 2014: 131 · 2013: 66 · 2012: 9
- FWCI
- 17.92
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Center for Research Resources (P41-RR14075, BIRN002, U24 RR021382)
- National Institute on Aging (AG022381)
- National Institute of Neurological Disorders and Stroke (1S10RR023401, R01 NS052585-01, 1R01NS070963, 1S10RR023043, 1S10RR019307, 1R21NS072652-01)
- Ellison Medical Foundation
- National Institute of Biomedical Imaging and Bioengineering (R01EB006758)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- FreeSurfer, neuroimaging data analysis, cortical surface reconstruction, T1-weighted imaging, brain connectivity, open source software
- MeSH terms
- Algorithms, Brain, Brain Mapping, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Software, History, 20th Century, History, 21st Century
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