A New MRI Masking Technique Based on Multi‐Atlas Brain Segmentation in Controls and Schizophrenia: A Rapid and Viable Alternative to Manual Masking

Brain masking of MRI images separates brain from surrounding tissue and its accuracy is important for further imaging analyses. We implemented a new brain masking technique based on multi‐atlas brain segmentation (MABS) and compared MABS to masks generated using FreeSurfer (FS; version 5.3), Brain Extraction Tool (BET), and Brainwash, using manually defined masks (MM) as the gold standard. We further determined the effect of different masking techniques on cortical and subcortical volumes generated by FreeSurfer.

[1]  Torsten Rohlfing,et al.  Performance-based classifier combination in atlas-based image segmentation using expectation-maximization parameter estimation , 2004, IEEE Transactions on Medical Imaging.

[2]  R. McCarley,et al.  Clinical high risk and first episode schizophrenia: Auditory event-related potentials , 2015, Psychiatry Research: Neuroimaging.

[3]  Max A. Viergever,et al.  Automatic Morphology-Based Brain Segmentation (MBRASE) from MRI-T1 Data , 2000, NeuroImage.

[4]  T. Woo,et al.  Analysis of schizophrenia-related genes and electrophysiological measures reveals ZNF804A association with amplitude of P300b elicited by novel sounds , 2014, Translational Psychiatry.

[5]  Dinggang Shen,et al.  Robust Deformable-Surface-Based Skull-Stripping for Large-Scale Studies , 2011, MICCAI.

[6]  Daniel Rueckert,et al.  Multiclassifier Fusion in Human Brain MR Segmentation: Modelling Convergence , 2006, MICCAI.

[7]  David R. Haynor,et al.  Nonrigid multimodality image registration , 2001, SPIE Medical Imaging.

[8]  Kwanghoon Sohn,et al.  Automated cerebrum segmentation from three-dimensional sagittal brain MR images , 2002, Comput. Biol. Medicine.

[9]  R. Leahy,et al.  Magnetic Resonance Image Tissue Classification Using a Partial Volume Model , 2001, NeuroImage.

[10]  David R. Haynor,et al.  PET-CT image registration in the chest using free-form deformations , 2003, IEEE Transactions on Medical Imaging.

[11]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[12]  Sébastien Ourselin,et al.  Brain MAPS: An automated, accurate and robust brain extraction technique using a template library , 2011, NeuroImage.

[13]  S. Woods,et al.  Chlorpromazine equivalent doses for the newer atypical antipsychotics. , 2003, The Journal of clinical psychiatry.

[14]  Anders M. Dale,et al.  A hybrid approach to the Skull Stripping problem in MRI , 2001, NeuroImage.

[15]  R. Bajcsy,et al.  A computerized system for the elastic matching of deformed radiographic images to idealized atlas images. , 1983, Journal of computer assisted tomography.

[16]  Bilwaj Gaonkar,et al.  Multi-atlas skull-stripping. , 2013, Academic radiology.

[17]  R. Kawashima,et al.  Automatic Brain Tissue Extraction Method Using Erosion-Dilation Treatment (BREED) From Three-Dimensional Magnetic Resonance Imaging T1-Weighted Data , 2002, Journal of computer assisted tomography.

[18]  Martha Elizabeth Shenton,et al.  On evaluating brain tissue classifiers without a ground truth , 2007, NeuroImage.

[19]  D. Louis Collins,et al.  BEaST: Brain extraction based on nonlocal segmentation technique , 2012, NeuroImage.

[20]  D. Collins,et al.  Automatic 3D Intersubject Registration of MR Volumetric Data in Standardized Talairach Space , 1994, Journal of computer assisted tomography.

[21]  R. Bajcsy,et al.  Elastically Deforming 3D Atlas to Match Anatomical Brain Images , 1993, Journal of computer assisted tomography.

[22]  Arthur W. Toga,et al.  Skull-stripping magnetic resonance brain images using a model-based level set , 2006, NeuroImage.

[23]  M. Stella Atkins,et al.  Fully automatic segmentation of the brain in MRI , 1998, IEEE Transactions on Medical Imaging.

[24]  W. A. Hanson,et al.  Interactive 3D segmentation of MRI and CT volumes using morphological operations. , 1992, Journal of computer assisted tomography.

[25]  Mark W. Woolrich,et al.  Bayesian analysis of neuroimaging data in FSL , 2009, NeuroImage.

[26]  Milan Sonka,et al.  3D Slicer as an image computing platform for the Quantitative Imaging Network. , 2012, Magnetic resonance imaging.

[27]  A. Traboulsee,et al.  MRI Brain Extraction with Combined Expectation Maximization and Geodesic Active Contours , 2006, 2006 IEEE International Symposium on Signal Processing and Information Technology.

[28]  Anders M. Dale,et al.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.

[29]  Aaron Carass,et al.  Simple paradigm for extra-cerebral tissue removal: Algorithm and analysis , 2011, NeuroImage.

[30]  Robert T. Schultz,et al.  Segmentation and Measurement of the Cortex from 3D MR Images , 1998, MICCAI.

[31]  William M. Wells,et al.  Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation , 2004, IEEE Transactions on Medical Imaging.

[32]  Brian B. Avants,et al.  Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain , 2008, Medical Image Anal..

[33]  Nikos Makris,et al.  Automatically parcellating the human cerebral cortex. , 2004, Cerebral cortex.

[34]  U Tiede,et al.  3-D segmentation of MR images of the head for 3-D display. , 1990, IEEE transactions on medical imaging.

[35]  Paul M. Thompson,et al.  Robust Brain Extraction Across Datasets and Comparison With Publicly Available Methods , 2011, IEEE Transactions on Medical Imaging.

[36]  Bennett A Landman,et al.  Non-local statistical label fusion for multi-atlas segmentation , 2013, Medical Image Anal..

[37]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[38]  Guang H. Yue,et al.  Automated Histogram-Based Brain Segmentation in T1-Weighted Three-Dimensional Magnetic Resonance Head Images , 2002, NeuroImage.

[39]  Koenraad Van Leemput,et al.  Automated model-based tissue classification of MR images of the brain , 1999, IEEE Transactions on Medical Imaging.