FreeSurfer.
- Authors
- Fischl, Bruce
- Year
- 2012
- Journal
- NeuroImage
- PMID
- 22248573
- DOI
- 10.1016/j.neuroimage.2012.01.021
- PMCID
- PMC3685476
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.
Left: examples of two geometrically different topological defects that are topologically equivalent: a handle that bridges a sulcus, and a hole in the bank of a gyrus. Right: a graphical example of the difficulty of using surface deformation techniques to model the cortical surface. Typically we want a smooth surface, but much of the cortical surface is buried deep inside folds forcing surfaces to pass through regions (indicated by the blue arrow) where the evolving surface has to bunch up to get enough surface area inside the fold to model the surface. Another problem is finding energy terms that will draw the surface into the deep fissure, and away from the narrow opening, which also means pulling it away from the true cortical surface to traverse the sulcal opening and arrive at the boundary on the other side.
Left: the approach taken with deformable models. A surface of known topology but incorrect geometry (a sphere) is driven by an energy functional towards the desired pial surface shown in red. The difficulty stems from finding terms that will generate a smooth surface but will allow it to pass through an intermediate representation that can push enough surface area into e.g. the sylvian fissure. Right: in contrast, deforming the topologically incorrect surface model outwards to the surface of the sphere is a relatively simple computational problem.
Example of a topological defect (left), an inaccurate correction (center) and an accurate correction (right) (thanks to Florent Ségonne).
Example of a surface defect (left), and it's representation in two orthogonal slices (center and right). The red portion in the left-hand image represents the region found to contain the defect. The red portion of the surface in the center and right images represent the surface that has been added to fill the hole.
| Name | Type |
|---|---|
| acceleration local | phenotype |
| age | phenotype |
| aging | phenotype |
| amygdala | anatomy |
| analysis degrees of freedom local | phenotype |
| brain structure | anatomy |
| Brodmann areas local | anatomy |
| caudate nucleus | anatomy |
| cerebrospinal fluid | drug |
| cognitive measures | phenotype |
| control population | cohort |
| cortex | anatomy |
| Cortical folding patterns local | anatomy |
| cortical gray matter thickness local | anatomy |
| cortical surface | anatomy |
| cortical surface models local | drug |
| cortical thickness | phenotype |
| cortical thickness measures local | phenotype |
| deep folds local | anatomy |
| deep sulci local | anatomy |
| dipoles | drug |
| disease population local | cohort |
| disease state | phenotype |
| early visual cortex local | anatomy |
| EEG | phenotype |
| EEG/MEG signal local | drug |
| EEG/MEG source estimation local | phenotype |
| FreeSurfer | drug |
| frontal cortex | anatomy |
| functional data local | phenotype |
| gray matter | anatomy |
| gray/white boundary | anatomy |
| gray/white matter interface local | anatomy |
| gyral cortex local | anatomy |
| gyrus local | anatomy |
| healthy development local | phenotype |
| hippocampal subfields local | anatomy |
| Hippocampal subfields local | anatomy |
| hippocampus | anatomy |
| histological thickness measures local | phenotype |
| human brain | anatomy |
| inverse problem local | phenotype |
| layer I local | anatomy |
| manual MRI measures local | phenotype |
| MEG local | phenotype |
| morphometric changes local | phenotype |
| motor cortex | anatomy |
| MRI volume local | drug |
| myelin | phenotype |
| neuroanatomical variability local | phenotype |
| neurological disorders | phenotype |
| neuropsychological variables local | phenotype |
| overall average cortical thickness local | phenotype |
| pallidum | anatomy |
| pial surface | anatomy |
| primary visual cortex | anatomy |
| pyramidal neurons | anatomy |
| scanner platform local | phenotype |
| sequence type local | phenotype |
| somatosensory cortex | anatomy |
| subcortical regions | anatomy |
| sulcal cortex local | anatomy |
| sulci | anatomy |
| sulcus local | anatomy |
| surface accuracy local | phenotype |
| surface misplacement local | phenotype |
| thalamus | anatomy |
| topological defects local | phenotype |
| von Economo average thickness measures local | phenotype |
| voxel geometry local | phenotype |
| voxels local | phenotype |
| white matter | anatomy |
| White matter fascicles local | anatomy |
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In this knowledge base
External
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| Magnetic Resonance Imaging Textural Changes Are More Sensitive Than Volumetric Changes in the Amygdala of Cocaine Use Disorder Patients. | Nandi S et al. | — | 2026 | → |
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| Exploring the Relationship Between White Matter Tracts and Resting-State Functional Language Lateralization Index. | Desjardins MÈ et al. | — | 2025 | → |
| Extending the ALPS index: Associating whole-brain patterns with glymphatic-related diffusion metrics in multiple sclerosis. | Santaniello SD et al. | — | 2025 | → |
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| From Bedside to Desktop: A Data Protocol for Normative Intracranial EEG and Abnormality Mapping. | Woodhouse H et al. | — | 2025 | → |
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| Functional and Structural Neural Plasticity Following sEMG Control of a Virtual Prosthetic Hand in an Individual with Bilateral Upper-Limb Congenital Amputation. | Feldman DA et al. | — | 2025 | → |
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| Functional Connectivity and Volumetrics Improve Outcome Prediction for Deep Brain Stimulation in Parkinson's Disease. | Younce JR et al. | — | 2025 | → |
| Functional connectivity profiles of amygdala subregions in posttraumatic stress disorder. | Haris EM et al. | — | 2025 | → |
| Functional hearing difficulties in Veterans with blast and blunt head trauma are associated with reduced fractional anisotropy in putative auditory radiations. | Poliva O et al. | — | 2025 | → |
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| Genetically Informed Disassortative Brain Morphometric Similarities Revealing Suicide Risk in Bipolar Disorder. | Wang T et al. | — | 2025 | → |
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| Genetic foundations of interindividual neurophysiological variability. | da Silva Castanheira J et al. | — | 2025 | → |
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| Psychosocial behavioral phenotypes of racially/ethnically minoritized older adults enrolled in HABS-HD differ on neuroimaging measures of brain age gap, hippocampal volume, and cortical thickness. | Clark AL et al. | — | 2025 | → |
| Psychotic-Like Experiences and White Matter Microstructure: A Fixel-Based Analysis Approach With Robust Replication Across Two Cohorts. | Goodwin I et al. | — | 2025 | → |
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| Quantifying Longitudinal Microstructural Changes in Mild Traumatic Brain Injury Patients with Mean Apparent Propagator MRI. | Gangolli M et al. | — | 2025 | → |
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| Quantitative brain volumetry in neurological disorders: from disease mechanisms to software solutions. | Marek J et al. | — | 2025 | → |
| Quantitative Measurement of Tau Burden in a Dual-Time-Window Dynamic PET Imaging Protocol with [<sup>18</sup>F]MK6240. | Xia Y et al. | — | 2025 | → |
| Quantitative susceptibility mapping at 7T as a biomarker of post- and interictal extravascular iron in patients with focal epilepsy. | Held NR et al. | — | 2025 | → |
| Quantitative susceptibility mapping in magnetically inhomogeneous tissues. | Jochmann T et al. | — | 2025 | → |
| Quantitative T<sub>1</sub> and Effective Proton Density (PD*) mapping in children and adults at 7T from an MP2RAGE sequence optimised for uniform T<sub>1</sub>-weighted (UNI) and FLuid And White matter Suppression (FLAWS) contrasts. | Dokumacı AS et al. | — | 2025 | → |
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| Reductions in brainstem volume as a key macrostructural indicator in at-risk populations for Alzheimer's disease. | Lancaster TM et al. | — | 2025 | → |
| Regional associations between cerebrovascular disease and cholinergic white matter pathways in the Lewy body continuum. | Rennie A et al. | — | 2025 | → |
| Regional Brain Volume and Cortical Thickness Mediate Age-Related Differences in Eye Movement Control. | Etteldorf R et al. | — | 2025 | → |
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| Regional effects of gantenerumab on neuroimaging biomarkers in the DIAN-TU-001 trial. | McCullough A et al. | — | 2025 | → |
| Regional gray matter volume is associated with motor imagery performance in children with and without developmental coordination disorder. | Mukherjee M et al. | — | 2025 | → |
| Regional specificity of the cingulate cortex thickness association with the intensity of psilocybin experience: a replication study. | Greguš D et al. | — | 2025 | → |
| Region-based U-nets for fast, accurate, and scalable deep brain segmentation: Application to Parkinson Plus Syndromes. | Li M et al. | — | 2025 | → |
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| Region-specific drivers of CSF mobility measured with MRI in humans. | Hirschler L et al. | — | 2025 | → |
| Relating Scene Memory and Perception Activity to Functional Properties, Networks, and Landmarks of Posterior Cerebral Cortex-A Probabilistic Atlas. | Steel A et al. | — | 2025 | → |
| Relationship Between Synaptic Density and Cortical (Micro)structure in Healthy Participants, Patients With Schizophrenia Spectrum Disorder, and Unaffected Siblings: A Multimodal [<sup>11</sup>C]UCB-J Positron Emission Tomography and Magnetic Resonance Imaging Study. | de Jager JE et al. | — | 2025 | → |
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| Sex-related differences and associated transcriptional signatures in the brain ventricular system and cerebrospinal fluid development in full-term neonates. | Sun Y et al. | — | 2025 | → |
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