Sulci as Landmarks

Mangin, Jean‐François; Auzias, Guillaume; Coulon, Olivier; Sun, Zhongyi; Rivière, Denis; Régis, Jean

doi:10.1016/b978-0-12-397025-1.00198-6

Cited by 11 publications

(11 citation statements)

References 44 publications

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“…We make no claims that this set of AFIDs is optimal and in the future, other locations may prove to be more effective than others. Also, for this first proposed set of AFIDs, we limited our locations to deep structures where less intersubject variability exists compared to cortical features (Thompson et al, ); future extensions could include linking our workflow with cortical surface‐based (Fischl, ) and sulcal‐based (Hellier et al, ; Mangin et al, ; Perrot, Rivière, & Mangin, ) methods of spatial correspondence. Development of similar protocols for other neuroimaging modalities such as T2‐weighted or diffusion‐based contrasts may also be of value.…”

Section: Discussionmentioning

confidence: 99%

A framework for evaluating correspondence between brain images using anatomical fiducials

Lau

Parrent

DeMarco

et al. 2019

Human Brain Mapping

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Accurate spatial correspondence between template and subject images is a crucial step in neuroimaging studies and clinical applications like stereotactic neurosurgery. In the absence of a robust quantitative approach, we sought to propose and validate a set of point landmarks, anatomical fiducials (AFIDs), that could be quickly, accurately, and reliably placed on magnetic resonance images of the human brain. Using several publicly available brain templates and individual participant datasets, novice users could be trained to place a set of 32 AFIDs with millimetric accuracy. Furthermore, the utility of the AFIDs protocol is demonstrated for evaluating subject‐to‐template and template‐to‐template registration. Specifically, we found that commonly used voxel overlap metrics were relatively insensitive to focal misregistrations compared to AFID point‐based measures. Our entire protocol and study framework leverages open resources and tools, and has been developed with full transparency in mind so that others may freely use, adopt, and modify. This protocol holds value for a broad number of applications including alignment of brain images and teaching neuroanatomy.

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Section: Discussionmentioning

confidence: 99%

A framework for evaluating correspondence between brain images using anatomical fiducials

Lau

Parrent

DeMarco

et al. 2019

Human Brain Mapping

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“…Also, for this first proposed set of AFIDs, we limited our locations to deep structures where less inter-subject variability exists compared to cortical features (Thompson et al, 1996); future extensions could include linking our workflow with cortical surfacebased (B. Fischl, 2004) and sulcal-based (Hellier et al, 2003;Mangin et al, 2015;Perrot, Rivière, & Mangin, 2011) methods of spatial correspondence. Development of similar protocols for other neuroimaging modalities such as T2-weighted or diffusion-based contrasts may also be of value.…”

Section: Limitations and Future Workmentioning

confidence: 99%

A framework for evaluating correspondence between brain images using anatomical fiducials

Lau

Parrent

DeMarco

et al. 2018

Preprint

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First Research Excellence Fund to BrainsCAN, Brain Canada, and computational resource through Compute Canada.Abstract: Accurate spatial correspondence between template and subject images is a crucial step in neuroimaging studies and clinical applications like stereotactic neurosurgery. In the absence of a robust quantitative approach, we sought to propose and validate a set of point landmarks, anatomical fiducials (AFIDs), that could be quickly, accurately, and reliably placed on magnetic resonance images of the human brain. Using several publicly available brain templates and individual participant datasets, novice users could be trained to place a set of 32 AFIDs with millimetric accuracy. Furthermore, the utility of the AFIDs protocol is demonstrated for evaluating subject-to-template and template-to-template registration.Specifically, we found that commonly used voxel overlap metrics were relatively insensitive to focal misregistrations compared to AFID point-based measures. Our entire protocol and study framework leverages open resources and tools, and has been developed with full transparency in mind so that others may freely use, adopt, and modify. This protocol holds value for a broad number of applications including alignment of brain images and teaching neuroanatomy.Establishing spatial correspondence between images is a crucial step in neuroimaging studies enabling fusion of multimodal information, analysis of focal morphological differences, and comparison of withinand between-study data in a common coordinate space. Stereotaxy arose as a result of questions raised by scientists and surgeons interested in the physiology and treatment of focal brain structures (A. C. Evans,

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“…Future work will lead to assess one by one the added value of each sulcus in the normalization process, relative to its capacity at improving the alignment of architectural data like postmortem architectonic maps or in vivo fMRI maps (Mangin et al, 2015a). In a context where the amount of architectural information planned to be used for normalization is rapidly increasing, it would be important to discard the sulci generating misleading implicit or explicit constraints.…”

Section: The Cortical Folding Patternmentioning

confidence: 99%

“…While this observation is relatively intuitive regarding the cortical folding patterns and their disturbing variability, the successes of the multi-atlas strategy seem to prove that the situation is similar for simpler brain structures. The alignment of a specific sulcus across a group of subjects raises a lot of issues related to its variable interruptions and branches (Mangin et al, 2015a). Since registration techniques provide more meaningful alignment when dealing with similar patterns, normalization should be applied independently in subgroups of subjects with the same sulcus pattern, leading to several independent standard spaces.…”

Section: The Diffeomorphism Delusionmentioning

confidence: 99%

“…The concept of sulcal pattern is relatively easy to understand: for instance, the central sulcus exists either as one single continuous furrow, or as a split furrow in case of interruption at the level of the middle fronto-parietal "pli de passage", a transverse usually buried gyrus (Mangin et al, 2015a). In practice, clustering techniques are challenged because of the existence of continuous variations from one pattern to the other.…”

Section: The Diffeomorphism Delusionmentioning

confidence: 99%

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Spatial normalization of brain images and beyond

Mangin

Lebenberg

Lefranc

et al. 2016

Medical Image Analysis

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The deformable atlas paradigm has been at the core of computational anatomy during the last two decades. Spatial normalization is the variant endowing the atlas with a coordinate system used for voxel-based aggregation of images across subjects and studies. This framework has largely contributed to the success of brain mapping. Brain spatial normalization, however, is still ill-posed because of the complexity of the human brain architecture and the lack of architectural landmarks in standard morphological MRI. Multi-atlas strategies have been developed during the last decade to overcome some difficulties in the context of segmentation. A new generation of registration algorithms embedding architectural features inferred for instance from diffusion or functional MRI is on the verge to improve the architectural value of spatial normalization. A better understanding of the architectural meaning of the cortical folding pattern will lead to use some sulci as complementary constraints. Improving the architectural compliance of spatial normalization may impose to relax the diffeomorphic constraint usually underlying atlas warping. A two-level strategy could be designed: in each region, a dictionary of templates of incompatible folding patterns would be collected and matched in a way or another using rare architectural information, while individual subjects would be aligned using diffeomorphisms to the closest template. Manifold learning could help to aggregate subjects according to their morphology. Connectivity-based strategies could emerge as an alternative to deformation-based alignment leading to match the connectomes of the subjects rather than images.

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Sulci as Landmarks

Cited by 11 publications

References 44 publications

A framework for evaluating correspondence between brain images using anatomical fiducials

A framework for evaluating correspondence between brain images using anatomical fiducials

A framework for evaluating correspondence between brain images using anatomical fiducials

Spatial normalization of brain images and beyond

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