A Probabilistic Atlas and Reference System for the Human Brain

By John C. Mazziotta. 2001

898 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/67495b31d4526537fbbe61daca719ca355c3c865

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Citations in the corpus

A three-dimensional, histological and deformable atlas of the human basal ganglia. I. Atlas construction based on immunohistochemical and MRI data (2007, methodology): “We combined cryo sectioned data, a source of high resolution stained anatomy, and an electronically acquired MRI dataset as recommended by the human brain mapping consortium (Mazziotta et al., 2001).”
Multi-Method Analysis of MRI Images in Early Diagnostics of Alzheimer's Disease (2011, methodology): “Individual MRI volumes were registered to standard space using the ICBM152 template [39].”
Multi-Contrast Human Neonatal Brain Atlas: Application to Normal Neonate Development Analysis (2011, unknown): “1) similar to the concept for creating the adult group-averaged atlas (ICBM-152) (Mazziotta et al., 2001;Mazziotta et al., 1995) and the single-subject atlas (colin27)(Aubert -Broche et al., 2006;Collins et al., 1998;Holmes et al., 1998), all of which are commonly used in the neuroimaging community.”
Template-O-Matic: A toolbox for creating customized pediatric templates (2008, background): “The positive effects of this approach should be most visible in samples that clearly deviate from the “ standard samples ” that the processing algorithms have been designedupon,namelyyoungandhealthyCaucasiansasinthecaseof the MNI standard brain templates (Mazziotta et al., 1995, 2001).”
Longitudinal Mapping of Cortical Thickness and Brain Growth in Normal Children (2004, unknown): “, 1994) that creates a spherical mesh surface that is continuously deformed to fit a cortical surface tissue threshold intensity value (signal value, which best differentiates cortical CSF on the outer surface of the brain from the underlying cortical gray matter) from the brain volume aligned in st”
Performing Label-Fusion-Based Segmentation Using Multiple Automatically Generated Templates (2012, background): “…how well nonlinear registration algorithms are able to recover anatomical differences between subjects and between a subject and a neuroanatomical template [Grabner et al., 2006; Holmes et al., 1998; Mazziotta et al., 2001a], but do little in the way of accounting for other sources of error.”
Spontaneous brain activity and EEG microstates. A novel EEG/fMRI analysis approach to explore resting-state networks (2010, methodology): “In the current implementation of sLORETA, computations were made in a realistic head model (Fuchs et al., 2002), using the MNI152 template (Mazziotta et al., 2001), with the three-dimensional solution space restricted to cortical gray matter, as determined by the probabilistic Talairach atlas…”
Deep learning of joint myelin and T1w MRI features in normal-appearing brain tissue to distinguish between multiple sclerosis patients and healthy controls (2017, unknown): “, 2006), which was derived from the MNI152 template (Mazziotta et al., 2001), and the central voxel of each patch, to enhance the interpretability of the results.”
neuromaps: structural and functional interpretation of brain maps (2022, background): “, the MNI ICBM 152 template; [22, 49]); however, standardized triangular (i.”
Which fMRI clustering gives good brain parcellations? (2014, unknown): “Brain atlases come into play to provide a set of ROIs that cover the brain volume (among many others see e.g. Mazziotta et al. (2001); Tzourio-Mazoyer et al. (2002); Shattuck et al. (2008)).”
Hippocampal Contributions to Model-Based Planning and Spatial Memory (2019, unknown): “Lesion masks drawn in MNI space were subsequently overlaid on the Harvard-Oxford Structural Atlas) (Mazziotta et al., 2001) to estimate the extent of damage to the hippocampus (see Figure 1).”
Atlas-based whole brain white matter analysis using large deformation diffeomorphic metric mapping: Application to normal elderly and Alzheimer’s disease participants (2009, unknown): “…enables us to statistically analyze the whole brain and report abnormal areas using a common coordinate system, such as ICBM-152 space (Ashburner and Friston, 1999; Chiang et al., 2008; Good et al., 2001; Mazziotta et al., 2001; Tanabe et al., 1998; Wright et al., 1995; Oishi et al., in press).”