Hubbry Logo
Talairach coordinatesTalairach coordinatesMain
Open search
Talairach coordinates
Community hub
Talairach coordinates
logo
8 pages, 0 posts
0 subscribers
Be the first to start a discussion here.
Be the first to start a discussion here.
Talairach coordinates
Talairach coordinates
Talairach coordinates
View on Wikipedia
from Wikipedia
Sagittal view of cingulate region of human brain with a Talairach grid superimposed in accordance with standard locators

Talairach coordinates, also known as Talairach space, is a 3-dimensional coordinate system (known as an 'atlas') of the human brain, which is used to map the location of brain structures independent from individual differences in the size and overall shape of the brain. It is still common to use Talairach coordinates in functional brain imaging studies and to target transcranial stimulation of brain regions.[1] However, alternative methods such as the MNI Coordinate System (originated at the Montreal Neurological Institute and Hospital) have largely replaced Talairach for stereotaxy and other procedures.[2]

History

[edit]

The coordinate system was first created by neurosurgeons Jean Talairach and Gabor Szikla in their work on the Talairach Atlas in 1967, creating a standardized grid for neurosurgery.[3][4] The grid was based on the idea that distances to lesions in the brain are proportional to overall brain size (i.e., the distance between two structures is larger in a larger brain). In 1988 a second edition of the Talairach Atlas came out that was coauthored by Tournoux, and it is sometimes known as the Talairach-Tournoux system. This atlas was based on single post-mortem dissection of a human brain.[5]

The Talairach Atlas uses Brodmann areas as the labels for brain regions.[6]

Description

[edit]

The Talairach coordinate system is defined by making two anchors, the anterior commissure and posterior commissure, lie on a straight horizontal line.[7] Since these two points lie on the midsagittal plane, the coordinate system is completely defined by requiring this plane to be vertical. Distances in Talairach coordinates are measured from the anterior commissure as the origin (as defined in the 1998 edition). The y-axis points posterior and anterior to the commissures, the left and right is the x-axis, and the z-axis is in the ventral-dorsal (down and up) directions.[8] Once the brain is reoriented to these axes, the researchers must also outline the six cortical outlines of the brain: anterior, posterior, left, right, inferior, and superior.[9] In the 1967 atlas the left is with positive coordinates while in the 1988 atlas the left has negative coordinates.

By defining standard anatomical landmarks that could be identified on different subjects (the anterior and posterior commissures), it became easier to spatially warp an individual brain image obtained through Magnetic Resonance Imaging (MRI), positron emission tomography (PET) and other imaging methods to this standard Talairach space. One can then make inferences about tissue identity at a specific location by referring to the atlas.

Brodmann regions in neuroscience

[edit]
A colorized image of the Brodmann areas

The Brodmann areas is an illustration of a cytoarchitectonic map of the human brain that was published by Korbinan Brodmann in his 1909 monogram. Brodmann's map splits the cerebral cortex into 43 differing parts, which become visible in cell-body stained histological sections. Years later, a large group of neuroscientists still utilize Brodmann's map for the localization of neuroimaging data that is obtained in living human brains.[10]

Brodmann in relation to Talairach coordinates

[edit]

Some neuroimaging techniques, in fact, purported the use of Brodmann's area as a guideline for Talairach coordinates. Further, these technologies showcase that experimental tasks in a common reference space become possible through imaging the living human brain by registering function and having architectonic data performed and defined.

Brodmann's map proved useful in varying neuroimaging software packages and stereotaxic atlases, such as the Talairach atlas. This atlas also serves as a demonstration of the inherent problems (i.e., impressions of matches between areal borders and sulcal landmarks may lead to wrong conclusions in terms of localization of cytoarchitectonic borders or the usage of Brodmann's map without knowledge of the text that accompanies the drawing misleading researchers to false conclusions).[10]

Conversion to other coordinate systems

[edit]

Montreal Neurological Institute (MNI) templates

[edit]

The MNI coordinate system, also referred to as MNI space, are multiple stereotaxic brain coordinate systems created by the Montreal Neurological Institute and Hospital.[11][12][13] Similar to the Talairach coordinates, MNI coordinates can be used to describe the location of particular brain structures, without having to take into account any individual brain differences. However, as the Talairach system is "unrepresentative of the population at large", MNI coordinates were developed from MRI data garnered from many individuals, in an effort to create a neural coordinate system that could be more generalizable.[14] MNI coordinates have been matched to Tailarach coordinates to allow landmarks to correspond.[14]

The original MNI space was MNI 305, which was created from 305 Tailarach aligned images, from which a mean brain image was taken.[11][15] MNI 152 (also known as ICBM 152) was created later with higher resolution MRI images that were registered to MNI 305, and from which a mean was taken.[12][13][15] MNI 152 is itself further made up of different atlases, with different constraints, such as linearly/non-linearly aligned and symmetric or non-symmetric brain hemispheres.[12]

Most neuroimaging software packages are able to convert from Talairach to MNI coordinates. However, disparities between MNI and Talairach coordinates can impede the comparison of results across different studies. This problem is most prevalent in situations where coordinate disparities should be corrected to reduce error, such as coordinate-based meta-analyses. There is a possibility that these disparities can be assuaged through the Lancaster transform, which can be adopted in order to minimize the variability in the literature regarding spatial normalization strategies.[16]

Non-linear registration

[edit]

Non-linear registration is the process of mapping Talairach coordinates to subject-specific coordinates and generating a non-linear map in an attempt to compensate for actual shape differences between the two. Registration is usually nonlinear because the Talairach atlas is not a simple rigid transform (or even affine transform) of a subject brain.[17]

The Talairach atlas is still commonly used in terms of the neuroimaging techniques that are available, but the lack of a three-dimensional model of the original brain makes it difficult for researchers to map locations from three-dimensional anatomical MRI images to the atlas automatically. Previous methods such as MNI have tried to assuage this issue through linear and piecewise mapping between the Talairach and the MNI template, but can only account for differences in overall brain orientation and size and thus cannot correctly account for actual shape differences.[18]

Optimized high-resolution brain template (HRBT)

[edit]

Current target brains are not suitable for current research (i.e., are average, can only be used in low-resolution MRI target brain mapping studies or are single brain). Optimized high-resolution brain template (HRBT), a high-resolution MRI target brain, is a technique that can aid in the issues named above. This optimization can be performed to help reduce individual anatomical biases of the original ICBM HBRT. The optimized HRBT is more adept at anatomically matching groups of brains.[19]

References

[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

Talairach coordinates

View on Grokipedia
from Grokipedia
Talairach coordinates constitute a three-dimensional stereotaxic for mapping and standardizing structures, enabling precise localization in , functional studies, and by aligning individual to a common reference space. Developed in the mid-20th century, this relies on the (AC) and (PC) as key landmarks, with the origin at the AC, the y-axis along the AC-PC line, and the x- and z-axes perpendicular to it, allowing for proportional adjustments to accommodate inter-individual anatomical variability. The framework originated from the work of French neurosurgeon Jean Talairach at Hôpital Sainte-Anne in during the 1950s, initially based on cadaveric studies and contrast ventriculography to target deep structures indirectly. Talairach's first atlas, published in 1957 with collaborators including Pierre Tournoux, introduced early stereotaxic principles, but the seminal 1988 Co-Planar Stereotaxic Atlas of the Human Brain refined the system with a digitized, proportional grid derived from a single post-mortem specimen, incorporating detailed coronal sections and labels for gyri, nuclei, and Brodmann areas. This atlas employed a 9-parameter to normalize images, reducing variability and facilitating comparisons across subjects in like PET and fMRI. Despite its foundational role in revolutionizing stereotactic procedures—such as and lesioning—Talairach coordinates have limitations, including reliance on a single reference brain and inconsistencies in three-dimensional representation, prompting the development of probabilistic atlases like those in MNI space. Nonetheless, the system remains a standard for reporting activation foci in research and clinical applications, influencing over decades of advancements.

Historical Background

Origins in Neurosurgery

Jean Talairach, a French neurosurgeon at Hôpital Sainte-Anne in , pioneered stereotactic in the 1950s as a means to treat severe psychiatric disorders through precise targeting of deep structures, particularly the and the anterior limb of the . This approach emerged from the limitations of earlier psychosurgical techniques like leucotomy, which lacked accuracy and often resulted in unintended side effects due to the 's anatomical complexity. Talairach's methods employed ventriculography—a radiographic technique using contrast agents to visualize the —for intraoperative localization, combined with to create targeted lesions. A major challenge in these procedures was the significant inter-individual variability in brain size, shape, and internal anatomy, which rendered traditional bony landmarks unreliable for guiding instruments to subcortical targets. To address this, Talairach developed an adjustable stereotactic frame designed to accommodate diverse human brain morphologies while ensuring reproducible positioning. In 1952, he proposed using the anterior commissure (AC) and posterior commissure (PC)—two midline structures visible on ventriculograms—as fixed reference points to establish a standardized coordinate system, forming the bicommissural line as the foundational axis for spatial orientation. Talairach's early work relied on human cadaver brains to validate and refine surgical planning, with studies of 100 postmortem specimens in 1957 yielding the first stereotaxic atlas of the and , which provided anatomical coordinates for clinical applications. This atlas facilitated coordinate-based targeting in living patients by correlating radiographic images with histological sections. In 1967, Talairach collaborated with radiologist Gábor Szikla to produce an advanced stereotaxic atlas of the telencephalon, further integrating ventriculography to map coordinates for precise neurosurgical interventions.

Publication of the Atlas

The definitive publication of the Talairach coordinate system occurred in 1988 with the release of Co-Planar Stereotaxic Atlas of the Human Brain: Three-Dimensional Proportional System—An Approach to Cerebral Imaging by Jean Talairach and Pierre Tournoux, published by Thieme Medical Publishers. This atlas standardized the system for broader anatomical referencing in and , deriving its structure from detailed tracings of post-mortem sections obtained from a single 60-year-old female subject. The work emphasized a proportional approach to accommodate variations in brain size while maintaining precise localization, marking a shift from earlier, more limited stereotaxic methods. Central to the atlas is the introduction of a proportional stereotaxic grid that enables three-dimensional coordinate assignment across the , facilitating the correlation of with anatomical landmarks. The atlas comprises a comprehensive series of high-detail color tracings in coronal, sagittal, and axial (horizontal) orientations, providing visual representations of structures for stereotaxic and . These sections are annotated with cytoarchitectonic regions, including Brodmann areas, to support functional and structural interpretations in clinical and research contexts. This 1988 publication evolved from Talairach's earlier collaborative efforts, particularly the 1967 Atlas d'Anatomie Stéréotaxique du Télencéphale co-authored with Gábor Szikla, which focused on telencephalic structures using initial stereotaxic techniques developed during neurosurgical applications in the 1960s. By incorporating a full three-dimensional framework, the 1988 atlas expanded the utility of the coordinate system beyond intraoperative guidance to serve as a reference for cerebral imaging modalities like computed tomography and magnetic resonance imaging.

System Fundamentals

Coordinate Axes and Landmarks

The Talairach coordinate system provides a standardized three-dimensional framework for specifying locations within the human brain, relying on key anatomical landmarks to account for inter-individual variability. The origin is defined at the anterior commissure (AC), a bundle of white matter fibers connecting the temporal lobes, located at coordinates (0, 0, 0). The posterior commissure (PC), another white matter structure bridging the midbrain, defines the AC-PC line, which serves as the primary orienting axis for the system. The midsagittal plane, representing the brain's midline of symmetry that separates the left and right hemispheres, establishes the reference for laterality, with the plane corresponding to x = 0. These landmarks enable precise, reproducible positioning independent of external cranial features. The system's Cartesian axes are oriented relative to these landmarks: the x-axis traverses the left-right dimension, with positive values extending to the right of the midsagittal plane; the y-axis aligns with the anterior-posterior direction along the AC-PC line, with positive values directed anteriorly from the AC; and the z-axis follows the inferior-superior trajectory, perpendicular to the AC-PC line, with positive values pointing superiorly from the AC. This configuration positions the AC-PC line parallel to the y-axis and ensures the z-axis remains orthogonal to it, creating a consistent geometric foundation. The formalization of these axes traces to the stereotaxic atlas developed by Talairach and Tournoux. Alignment to the Talairach system begins with identifying the AC and PC in brain images, followed by rotation and translation to position the AC-PC line parallel to the y-axis and the midsagittal plane perpendicular to the x-axis. This step corrects for variations in head posture and orientation, aligning the structure to the standard frame before any scaling is applied. The resulting coordinate space encompasses typical ranges derived from the atlas : x from -68 to +68 mm (spanning left to right hemispheres), y from -86 to +86 mm (from posterior occipital regions to anterior frontal areas), and z from -40 to +78 mm (from inferior to superior parietal cortex). These dimensions reflect the proportional extents of the used in the system.

Atlas Composition and Proportions

The Talairach atlas employs a proportional grid system to standardize brain anatomy across individuals by linearly scaling images to match the dimensions of a single reference brain. This system divides the brain into distinct compartments along three primary dimensions: anterior-posterior, superior-inferior, and left-right. In the anterior-posterior direction, the grid is segmented by the anterior commissure (AC) and posterior commissure (PC), creating an anterior compartment from the frontal pole to the AC, a central compartment from the AC to the PC, and a posterior compartment from the PC to the occipital pole. The superior-inferior dimension is divided into superior (above the AC-PC line) and inferior (below the AC-PC line) compartments, with the horizontal plane aligned to the mid-commissural (AC-PC) line. Scaling is based on measurements to the most superior and most inferior points of the cerebrum. The left-right dimension is partitioned by the interhemispheric fissure into medial and lateral compartments relative to the midline of each hemisphere. Scaling within this grid applies linear proportions to account for inter-subject variability, using the reference brain's AC-PC distance of 23 mm as the baseline for normalization. Individual brains are measured for their corresponding dimensions, and piecewise linear transformations are computed for each of the 12 resulting compartments to map them onto the atlas space. This approach enables the alignment of diverse brain sizes and shapes through simple affine adjustments, including translations, rotations, and scalings, without requiring complex non-linear deformations. The atlas itself is composed from detailed anatomical data derived from a single postmortem of a 60-year-old woman, featuring photographic plates of histological sections supplemented by overlays of sulcal patterns, gyral boundaries, myeloarchitectonic features, subcortical nuclei, and cortical layer delineations. These elements provide comprehensive labeling for both cortical and subcortical structures, with Brodmann areas and vascular landmarks integrated for reference. The use of a single as the basis, while enabling precise internal consistency, introduces limitations such as potential inaccuracies in regions with high inter-individual variability, where linear scaling may fail to capture non-linear anatomical distortions like irregular sulcal folding or volumetric differences in deep nuclei.

Uses in Neuroscience

Reporting Brain Locations

In neuroimaging research, Talairach coordinates are routinely used to specify the precise three-dimensional locations of activations or lesions, particularly in studies employing (fMRI), (PET), and (EEG) source localization. Researchers report peak activation sites as (x, y, z) triplets in Talairach space, where x denotes the left-right axis (positive for right hemisphere), y the anterior-posterior axis (positive anterior to the ), and z the inferior-superior axis (positive above the anterior commissure-posterior commissure line). This standardized reporting enables coordinate-based meta-analyses, such as activation likelihood estimation (ALE), by pooling foci from multiple experiments to identify convergent regions across datasets. The use of Talairach coordinates provides essential historical compatibility for integrating findings from the and early , a period when this system dominated due to its basis in the 1988 Talairach atlas and widespread adoption in early PET and fMRI protocols. For example, meta-analyses of language processing often cite activations in at approximately (-50, 20, 10), corresponding to the left , while hand-related activity in the is frequently localized near (-34, -19, 57). These examples illustrate how Talairach reporting facilitates precise localization of functional regions, supporting cross-study comparisons without requiring full image datasets. Although the Montreal Neurological Institute (MNI) template has become the preferred standard in modern for its probabilistic representation of population variability, Talairach coordinates retain relevance in specific applications. They are still employed in neurosurgical planning for stereotactic targeting, where the atlas's proportional scaling aids in aligning patient-specific imaging with anatomical landmarks. Additionally, databases like BrainMap archive thousands of activation foci in Talairach space, enabling ongoing meta-analyses of historical and legacy datasets. These coordinates can also be briefly related to Brodmann areas for enhanced functional interpretation in reporting.

Integration with Brodmann Areas

defined 52 cytoarchitectonic areas of the human in 1909, delineating them based on variations in cellular and layering observed through microscopic examination. These areas provided a foundational parcellation for correlating with function. The Talairach atlas incorporates an overlay of Brodmann's onto its stereotaxic sections, labeling 47 of these areas to facilitate anatomical reference in three-dimensional space, though boundaries between adjacent areas are not always explicitly defined in the atlas plates. This integration allows researchers to approximate the location of functional activations relative to cytoarchitectonic regions using Talairach coordinates. Representative mappings illustrate this correspondence; for instance, Brodmann area 17, corresponding to the , is centered approximately at (0, -90, 0) in Talairach space along the . Similarly, , associated with the , is located around (-45, 35, 25) in the left hemisphere, reflecting its position on the . These coordinates serve as probabilistic centroids, enabling the localization of activations to specific functional-anatomical zones without direct histological verification. Challenges in mapping arise from intersubject variability in sulcal landmarks and brain morphology, which prevent exact one-to-one correspondences between Talairach coordinates and Brodmann boundaries, often resulting in probabilistic rather than deterministic assignments. Surface-based analyses reveal significant differences in area size, shape, and sulcal relationships across individuals, complicating precise overlays. To address this, tools like the Talairach Daemon provide approximate Brodmann labeling by querying a database of atlas-derived volumes for given coordinates, extending searches to nearby regions when exact matches are unavailable. Historically, the integration of Brodmann areas with Talairach coordinates played a pivotal role in early (fMRI) studies during the , allowing researchers to link observed activations to presumed cytoarchitectonic regions without relying on postmortem from individual subjects. This approach standardized reporting in , as activations were routinely described using Talairach coordinates alongside estimated Brodmann areas to infer functional roles.

Transformations to Modern Systems

Standard MNI Conversions

The Montreal Neurological Institute (MNI) space serves as a standardized probabilistic atlas derived from averaged (MRI) scans, facilitating cross-subject comparisons in . The original MNI305 template was constructed by averaging 305 T1-weighted MRI scans from young adults, with each scan linearly transformed into Talairach space to create a low-resolution (2 mm isotropic) reference brain. Subsequently, the MNI152 template improved upon this by averaging 152 high-resolution (1 mm isotropic) T1-weighted MRI scans from a similar cohort, with linear registration to the MNI305 to enhance contrast and anatomical detail while maintaining compatibility. Like the Talairach system, MNI space defines its origin at the (AC), but it exhibits distinct scaling and proportions due to the averaging process across diverse brain sizes, resulting in a template approximately 24% larger in volume than the Talairach brain. Standard conversions between Talairach and MNI coordinates rely on linear transformations, specifically 12-parameter affine registrations that align the anterior-posterior commissure (AC-PC) line and account for differences in , , scaling, and shearing. These transformations minimize spatial discrepancies by fitting the Talairach-defined landmarks to the MNI template's , addressing biases such as the MNI 's larger , more nose-down orientation, and slight downward relative to Talairach. A widely used implementation is the icbm2tal algorithm, which applies a composite affine transform derived from the ICBM-152 template to perform batch conversions, reducing average coordinate disparities to under 2 mm in deep structures. This 12-parameter approach includes three translations, three rotations, three isotropic scalings, and three shearing parameters, with notable scaling differences like approximate factors of x ≈ 1.06, y ≈ 1.05, z ≈ 1.11 (based on FSL-derived icbm2tal transform) when mapping from Talairach to MNI space. The full linear transformation employs a 4x4 affine matrix, such as the one for MNI to Talairach conversion in tools like icbm2tal, which incorporates specific scaling and translation terms to align the ellipsoidal disparity pattern observed between the spaces. These standard MNI conversions are essential for integrating legacy Talairach-based datasets into modern analysis pipelines, such as (SPM) or FSL software, which natively operate in MNI space to enable meta-analyses and group-level inferences. By applying icbm2tal or equivalent linear methods, researchers can transform historical stereotactic coordinates from neurosurgical or early studies, preserving their utility in contemporary probabilistic atlases without requiring nonlinear warping.

Enhanced Registration Techniques

Non-linear registration techniques have been developed to address the limitations of linear transformations when aligning Talairach coordinates to modern spaces like MNI, particularly by accounting for the anatomical variability arising from Talairach's basis in a single postmortem compared to the population-averaged MNI template. Deformable models, such as FNIRT implemented in the FSL software library, enable voxel-wise adjustments that capture subtle shape differences, improving alignment accuracy especially in regions with high inter-subject variability. These methods reduce systematic biases, such as the elongated shape of the MNI template relative to the Talairach , yielding more precise spatial mappings for functional and structural analyses. Specialized templates further enhance registration by providing high-fidelity targets for warping Talairach coordinates. The optimized high-resolution brain template (HRBT), derived from MRI data, serves as an improved that minimizes individual anatomical biases inherent in the original Talairach atlas, facilitating more accurate nonlinear deformations. This template, with its detailed contrast and structure, is particularly valuable in applications like stereotactic radiosurgery, where precise subcortical targeting is essential. Additional approaches include symmetric diffeomorphic registration, as implemented in the ANTs toolbox, which preserves while modeling complex deformations between Talairach and MNI spaces through bidirectional mappings. Complementing this, multi-atlas fusion techniques propagate labels from multiple registered to a target, enhancing subcortical structure delineation and reducing errors from single-atlas reliance. These methods collectively improve localization accuracy in deep regions, where Talairach's proportional scaling can introduce distortions. Recent advancements up to 2025 incorporate AI-driven elements into normalization pipelines, with tools like FreeSurfer integrating for robust segmentation and alignment that better handle high-field MRI data, mitigating Talairach's outdated assumptions for contemporary imaging resolutions. Such integrations support more reliable transformations, particularly for diverse populations and ultra-high-resolution scans.

References

  1. https://thejns.org/focus/view/journals/neurosurg-focus/47/3/article-pE12.xml
  2. http://www.talairach.org/about.html
  3. https://www.mdpi.com/2076-3425/13/5/830
  4. https://pmc.ncbi.nlm.nih.gov/articles/PMC7592934/
  5. https://www.researchgate.net/publication/335565900_Jean_Talairach_a_cerebral_cartographer
  6. https://pmc.ncbi.nlm.nih.gov/articles/PMC6870828/
  7. http://s.mriquestions.com/uploads/3/4/5/7/34572113/talairachversusmni.pdf
  8. https://www.sciencedirect.com/science/article/abs/pii/S1053811912000419
  9. https://www.talairach.org/Lancaster_HBM_00.pdf
  10. https://www.talairach.org/about.html
  11. https://www.frontiersin.org/journals/neuroanatomy/articles/10.3389/fnana.2021.627656/full
  12. https://pmc.ncbi.nlm.nih.gov/articles/PMC7782399/
  13. https://pmc.ncbi.nlm.nih.gov/articles/PMC6871915/
  14. https://www.fieldtriptoolbox.org/faq/source/coordsys/
  15. https://www.brainvoyager.com/bv/doc/UsersGuide/BrainNormalization/AutomaticACPCAndTalairachTransformation.html
  16. https://afni.nimh.nih.gov/pub/dist/ASTON/afni08_talairach.pdf
  17. https://proceedings.neurips.cc/paper/2004/file/5df07ecf4cea616e3eb384a9be3511bb-Paper.pdf
  18. https://academic.oup.com/scan/article/2/2/150/2736775
  19. http://www2.psychology.uiowa.edu/classes/31231/Labs/Lab7/Fox_AnnReview_meta_analysis_2014.pdf
  20. https://neuroarts.org/pdf/broca%27s.pdf
  21. https://www.pnas.org/doi/10.1073/pnas.0702453104
  22. https://brainmap.org/pubs/FoxFNI94.pdf
  23. https://www.brainmap.org/
  24. https://pubmed.ncbi.nlm.nih.gov/10686118/
  25. https://jamanetwork.com/journals/jamapsychiatry/fullarticle/208942
  26. https://www.sciencedirect.com/science/article/abs/pii/S1053811999905165
  27. https://onlinelibrary.wiley.com/doi/abs/10.1002/1097-0193%28200007%2910:3%253C120::AID-HBM30%253E3.0.CO%3B2-8
  28. https://www.mcgill.ca/bic/software/tools-data-analysis/anatomical-mri/atlases/mni-305
  29. https://mcin.ca/research/neuroimaging-methods/atlases/
  30. https://www.brainmap.org/pubs/LancasterHBM07.pdf
  31. https://www.brainmap.org/icbm2tal/
  32. https://pmc.ncbi.nlm.nih.gov/articles/PMC2603575/
  33. https://web.mit.edu/fsl_v5.0.10/fsl/doc/wiki/FNIRT%282f%29UserGuide.html
  34. https://pmc.ncbi.nlm.nih.gov/articles/PMC6871323/
  35. https://pubmed.ncbi.nlm.nih.gov/12377166/
  36. https://mangoviewer.com/downloads/optimized_target_brain_colin.pdf
  37. https://pmc.ncbi.nlm.nih.gov/articles/PMC2276735/
  38. https://www.researchgate.net/publication/24043100_Multi-Atlas_based_segmentation_of_brain_images_Atlas_selection_and_its_effect_on_accuracy
  39. https://surfer.nmr.mgh.harvard.edu/fswiki/ReleaseNotes
  40. https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.26126
Add your contribution
Related Hubs
User Avatar
No comments yet.