Sequence-independent segmentation of magnetic resonance images.

By Bruce Fischl, David H. Salat, André J W van der Kouwe, Nikos Makris, Florent Ségonne, Brian T. Quinn, A. M. Dale. NeuroImage, 2004

2,207 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/48cc846be2997cd9bb19c14c932a88c07e716f86

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Bruce Fischl
2. Martin Reuter
3. H. Rosas
4. Bogdan Draganski
5. Lara M. Wierenga
6. Sarah Durston
7. Bob Oranje
8. Marieke Langen

In Radiology, Nuclear Medicine and Imaging

1. Bruce Fischl
2. Matthew F. Glasser
3. Randy L. Buckner
4. Martin Reuter
5. H. Rosas
6. D. V. Van Essen
7. Saâd Jbabdi
8. Timothy Edward John Behrens

Citations in the corpus

• Mapping Human Cortical Areas in vivo Based on Myelin Content as Revealed by T1- and T2-weighted MRI (2011, background): “…studies have shown regional differences in T1 or T1-weighted (T1w) image intensity in cortical gray matter, including differences between association cortices and primary sensory and motor cortices using surface (Fischl et al., 2004; Salat et al., 2009) and volume analyses (Steen et al., 2000).”
• Unique developmental trajectories of cortical thickness and surface area (2014, positive): “This labeling process involved surface inflation (Fischl et al., 1999) and registration to a spherical atlas based on subject specific cortical folding patterns (Fischl et al., 2004a,b).”
• Prolonged institutional rearing is associated with atypically larger amygdala volume and difficulties in emotion regulation (2010, neutral): “The automated procedures for volumetric measures of the different brain structures are described in detail by Fischl et al. (2002; 2004).”
• OASIS-3: Longitudinal Neuroimaging, Clinical, and Cognitive Dataset for Normal Aging and Alzheimer Disease (2019, neutral): “…folding patterns to match cortical geometry across subjects (Fischl et al., 1999b), parcellation of the cerebral cortex into units with respect to gyral and sulcal structure 37 (Fischl et al., 2004b), and creation of a variety of surface based data including maps of curvature and sulcal depth.”
• Toward in vivo histology: A comparison of quantitative susceptibility mapping (QSM) with magnitude-, phase-, and R2⁎-imaging at ultra-high magnetic field strength (2013, positive): “Thus, cortical mapping of the MRI signal has previously been proposed, as a means to study anatomical features in the cerebral cortex in vivo (Barbier et al., 2002; Bridge et al., 2005; Clark et al., 1992; Fischl et al., 2004; Glasser and van Essen, 2011; Salat et al., 2009; Turner et al., 2008).”
• Diffusion tensor imaging shows white matter tracts between human auditory and visual cortex (2011, positive): “normalized (Sled et al. 1998), subcortical volumetric structures were segmented ( Fischl et al. 2002, 2004a ) and the grey–white matter boundary was tesselated and topologic inaccuracies automatically corrected (Fischl et al. 2001; Segonne et al. 2007).”
• Automated Probabilistic Reconstruction of White-Matter Pathways in Health and Disease Using an Atlas of the Underlying Anatomy (2011, methodology): “The accuracy of the automated anatomical segmentation has addressed elsewhere (Fischl et al., 2002, 2004b).”
• MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field (2010, background): “…images also implies the potential to further improve the outcome of segmentation and classification algorithms that often struggle with distinguishing white matter from arteries (Fischl et al., 2004) and special algorithms have to be developed to remove this information (Penumetcha et al., 2008).”
• Visualization of image data from cells to organisms (2010, positive): “The FreeSurfer package, for instance, accomplishes this using a cortical surface matching technique that aligns brains on the basis of their cortical folding patterns and is widely used for detecting these brain changes, for populations and for single subjects over tim”
• FreeSurfer (2012, methodology): “This included automated geometric accurate topology correction (Fischl et al., 2001), surface-based inter-subject alignment (Fischl et al., 1999a, 1999b) and whole-brain segmentation (Fischl et al., 2002, 2004a).”
• Within-subject template estimation for unbiased longitudinal image analysis (2012, methodology): “The spherical registration (Fischl et al., 1999b) and cortical parcellation procedures (Fischl et al., 2004b; Desikan et al., 2006) establish a coordinate system for the cortex by warping individual surface models into register with a spherical atlas in a way that aligns the cortical folding…”