BrainSuite: An Automated Cortical Surface Identification Tool

By David W. Shattuck, Richard M. Leahy. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2000

933 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/7fb831b897af4f351967f311dd2bc601004c5bfd

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Citations in the corpus

The electric field in the cortex during transcranial current stimulation (2013, methodology): “The segmentation of these 1×1×1 mm3 resolution images was performed using Brainsuite (version 9.01, http://www.loni.ucla.edu/Software/ BrainSuite) (Dogdas et al., 2005; Shattuck and Leahy, 2001, 2002; Shattuck et al., 2001), with some adjustments of the default parameter values.”
The LONI Pipeline Processing Environment (2003, background): “…to hundreds of milliseconds before each individual command execution and are tunable for specific installations. have processed datasets where the Brain Extraction Tool (Smith, 2002) performs more reliably and ones where the Brain Surface Extractor (Shattuck and Leahy, 2002) performs more reliably.”
Visualization of image data from cells to organisms (2010, neutral): “…have been developed for the task of extracting, analyzing and visualizing models of the brain from MRI (for example, FreeSurfer 28 , BrainSuite 27 , BrainVoyager 29 , MedINRIA and BrainVisa 30 ), as have tools specific to cardiac image processing and analysis (for example, Cardiac Image…”
BioImage Suite: An integrated medical image analysis suite: An update. (2006, methodology): “The neuroimaging packages such as Slicer [19], Brainsuite [17] and SPM [20] are the best developed.”
Construction of a 3D probabilistic atlas of human cortical structures (2008, background): “The volunteer group was composed of 20 males and 20 females; average age at the time of image acquisition (mean±S.D.) was 29.20±6.30 years (min=19.3, max=39.5).”
AnoDDPM: Anomaly Detection with Denoising Diffusion Probabilistic Models using Simplex Noise (2022, methodology): “Therefore we applied the BrainSuite [22] bias field correction to the images.”
A curvature-based approach to estimate local gyrification on the cortical surface (2006, methodology): “First, we created an intracranial mask of the brain using a brain surface extraction algorithm tool (BSE) that is based on a combination of non-linear smoothing, edge finding and morphologic processing (Shattuck and Leahy, 2002).”
The Developing Human Connectome Project: a Minimal Processing Pipeline for Neonatal Cortical Surface Reconstruction (2017, methodology): “Once segmentations are extracted, surface mesh modelling approaches are, to an extent, agnostic of the origin of the data; allowing, in principle, the application of a wide variety of cortical mesh modelling approaches, to neonatal data, including those provided within the FreeSurfer (Dale et al., 1”
Detection of cortical thickness correlates of cognitive performance: Reliability across MRI scan sessions, scanners, and field strengths (2008, methodology): “…have been developed for segmenting and measuring the cerebral cortex from MRI data (Dale et al., 1999; Joshi et al., 1999; MacDonald et al., 1999; Xu et al., 1999; Zeng et al., 1999; van Essen et al., 2001; Shattuck and Leahy, 2002; Sowell et al., 2003; Barta et al., 2005; Han et al., 2005).”
Brain Functional Localization: A Survey of Image Registration Techniques (2007, methodology): “The tools listed in Table II are Surefit, based on the technique of Van Essen et al. [288], Freesurfer by Fischl et al. [281], [292], [293], BrainSuite by Shattuck and Leahy [294], and Cortical reconstruction using implicit surface evolution (CRUISE) by the Image Analysis and Communications group at”
Automated brain extraction of multisequence MRI using artificial neural networks (2019, methodology): “In contrast, average processing time of a single T1-w sequence with one of the six competing public brain extraction algorithms ranged from 3 s to 34.6 min (specifically, averages were 3 s for BSE, 17 s for BET, 1.4 min for ROBEX, 4.0 min for 3dSkullstrip, 10.7 min for BEaST, and 34.5 min for MONSTR”
Tensor-Based Morphometry as a Neuroimaging Biomarker for Alzheimer’s Disease: An MRI Study of 676 AD, MCI, and Normal Subjects (2008, neutral): “The MDT template was manually parcellated using the Brainsuite software program (Shattuck and Leahy, 2002) by a trained anatomist to generate binarymasks for frontal, parietal, temporal, and occipital lobes.”
FastSurfer - A fast and accurate deep learning based neuroimaging pipeline (2019, neutral): “To date, a few well maintained neuroimage processing pipelines such as FreeSurfer (Fischl et al., 2002), BrainSuite(Shattuck and Leahy, 2002), SPM (Friston et al., 2007), ANTs (Avants et al., 2009), or FSL (Jenkinson et al., 2012) are the only means available to process and evaluate the incoming ﬂ o”
Brainstorm: A User-Friendly Application for MEG/EEG Analysis (2011, methodology): “Three popular and freely available surface formats are supported: BrainSuite [31], BrainVISA [32], and FreeSurfer [33].”