This is a version of the ICBM Average Brain – an average of 152 T1-weighted MRI scans, linearly transformed to Talairach space – that is specially adapted for use with the MNI Linear Registration Package (mni_autoreg). Methods In 2001, within the ICBM project (Mazziotta et al., 1995, 2001a,b), three sites (MNI, UCLA, UTHSCSA) each collected…
The interpretation of magnetic resonance (MR) images of the human brain is facilitated when different data sets can be compared by visual inspection of equivalent anatomical planes. Quantitative analysis with pre-defined atlas templates often requires the initial alignment of atlas and image planes. A completely automatic method has been developed, to register a given volumetric…
MNI Average Brain (305 MRI) Stereotaxic Registration Model This is a version of the MNI Average Brain (an average of 305 T1-weighted MRI scans, linearly transformed to Talairach space) specially adapted for use with the MNI Linear Registration Package (mni_reg). Methods In order to overcome the idiosyncrasies of using a single subject brain as a…
Colin 27 Average Brain, Stereotaxic Registration Model, high-resolution version 2008 The anatomical phantom is derived from T1, T2, PD-weighted images formed from the average of 27, 11 and 12 scans respectively, of the same normal subject. These volumes are defined at a 0.5mm isotropic voxel grid in Talairach space, with dimensions 362*434*362 (XxYxZ) and start…
Stereotaxic Registration Model, original 1998 version This is a stereotaxic average of 27 T1-weighted MRI scans of the same individual. In 1998, a new atlas with much higher definition than MNI305s was created at the MNI. One individual (CJH) was scanned 27 times and the images linearly registered to create an average with high SNR…
MNI ICBM 152 non-linear 6th Generation Symmetric Average Brain Stereotaxic Registration Model This is a version of the ICBM Average Brain – an average of 152 T1-weighted MRI scans, linearly and non-linearly (6 iterations) transformed to form a symmetric model in Talairach space – that is specially adapted for use with the MNI Linear Registration Package…
Post-Doctoral Fellow I am currently a postdoctoral researcher at the Image Processing lab at McGill University. I obtained my B.Sc. and M.Sc. in Electrical Engineering, Control Systems and my Ph.D. in Biomedical Engineering. My current research is focused on vascular causes of dementia in neurodegenerative disease populations (i.e. Alzheimer’s disease, Parkinson’s disease, and frontotemporal dementia).…
We present an unbiased magnetic resonance imaging template brain volume for pediatric data from birth to 4.5y age range. These volumes were created using 317 scans from 108 children enrolled in the NIH-funded MRI study of normal brain development (Almli et al., 2007, Evans and Group 2006). Tools for using these atlases can be found…
We present an unbiased standard magnetic resonance imaging template brain volume for pediatric data from the 4.5 to 18.5y age range. These volumes were created using data from 324 children enrolled in the NIH-funded MRI study of normal brain development (Almli et al., 2007, Evans and Group 2006). Tools for using these atlases can be found…
A number of unbiased non-linear averages of the MNI152 database have been generated that combines the attractions of both high-spatial resolution and signal-to-noise while not being subject to the vagaries of any single brain (Fonov et al., 2011). The procedure involved multiple iterations of a process where, at each iteration, individual native MRIs were non-linearly…
