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Normalisation des données Oury Monchi, Ph. D. Centre de Recherche, Institut Universitaire de Gériatrie Normalisation des données Oury Monchi, Ph. D. Centre de Recherche, Institut Universitaire de Gériatrie de Montréal & Université de Montréal

Stereotaxic Space J. Talairach and P. Tournoux, Co-planar stereotactic atlas of the human brain: Stereotaxic Space J. Talairach and P. Tournoux, Co-planar stereotactic atlas of the human brain: 3 -Dimensional proportional system: an approach to cerebral imaging, Stuttgart, Georg Thieme Verlag, 1988 • based on anatomical landmarks (anterior and posterior commissures) • originally used to guide blind stereotaxic neurosurgical procedures (thalamotomy, pallidotomy) • now used by Neuro. Scientific community for interpretation and comparison of results

AC-PC line posterior commissure AC-PC line anterior commissure VAC AC-PC line posterior commissure AC-PC line anterior commissure VAC

Stereotaxic Space J Talairach & P Tournoux, Co-planar stereotaxic atlas of the human brain, Stereotaxic Space J Talairach & P Tournoux, Co-planar stereotaxic atlas of the human brain, Georg Thieme, 1988

Stereotaxic Space Stereotaxic Space

Anatomical variability remains Talairach & Tournoux Atlas, 1988 variability of central sulcus from 20 Anatomical variability remains Talairach & Tournoux Atlas, 1988 variability of central sulcus from 20 subjects

Not Registered Data Images courtesy A. Zijdenbos, MNI Not Registered Data Images courtesy A. Zijdenbos, MNI

Registered Data Registered Data

Registration to Stereotaxic Space Advantages for anatomical/structural imaging: • facilitates comparisons across – time Registration to Stereotaxic Space Advantages for anatomical/structural imaging: • facilitates comparisons across – time points – subjects – groups – sites • permits averaging between subjects to S/N • Allows the use of spatial masks for post-processing (anatomically driven hypothesis testing) • allows the use of spatial priors (classification) • allows the use of anatomical models (segmentation) • provides a framework for statistical analysis with wellestablished random field models • Allows the rapid re-analysis using different criteria

Registration to Stereotaxic Space Advantages for functional imaging: • Provides a conceptual framework for Registration to Stereotaxic Space Advantages for functional imaging: • Provides a conceptual framework for the completely automated, 3 D analysis across subjects. • Facilitate intra/inter-subject comparisons across – time points, subjects, groups, sites • Extrapolate findings to the population as a whole • Increase activation signal above that obtained from single subject • Increase number of possible degrees of freedom allowed in statistical model • Enable reporting of activations as co-ordinates within a known standard space – e. g. the space described by Talairach & Tournoux

Talairach Atlas Drawbacks for functional imaging: • is derived from an unrepresentative single 60 Talairach Atlas Drawbacks for functional imaging: • is derived from an unrepresentative single 60 -yr old female cadaver brain (when most functional activation studies are done on young living subjects!) • ignores left-right hemispheric differences • has variable slice separation, up to 4 mm • while it contains transverse, coronal and sagittal slices, it is not contiguous in 3 D

Stereotaxic Space However, the space and the stereotaxic concept are still worthwhile: • Provides Stereotaxic Space However, the space and the stereotaxic concept are still worthwhile: • Provides a conceptual framework for the completely automated, 3 D analysis across subjects. • Collins, L. , Evans A. , et al. have created a replacement target volume for stereotaxic mapping to address weaknesses of the Talairach atlas

Image Registration • Registration - i. e. Optimise the parameters that describe a spatial Image Registration • Registration - i. e. Optimise the parameters that describe a spatial transformation between the source and reference (template) images mritotal: créer la matrice de transformation. xfm • Transformation - i. e. Re-sample according to the determined transformation parameters p. ex: mincresample ou resample_tal: appliquer la transformation aux données

Idée de Neurolens Pourquoi normaliser des données fonctionnelles sur un ‘template’ anatomique. Création d’un Idée de Neurolens Pourquoi normaliser des données fonctionnelles sur un ‘template’ anatomique. Création d’un template T 2* Visualisation du processus d’optimisation!

Slides Aknowledgements Louis Collins, Montreal Neurological Institute Andrew Janke, Montreal Neurological Institute FSL & Slides Aknowledgements Louis Collins, Montreal Neurological Institute Andrew Janke, Montreal Neurological Institute FSL & Free. Surfer Course, f. MRIb, Oxford