Literature DB >> 15219598

Putting our heads together: a consensus approach to brain/non-brain segmentation in T1-weighted MR volumes.

Kelly Rehm1, Kirt Schaper, Jon Anderson, Roger Woods, Sarah Stoltzner, David Rottenberg.   

Abstract

We describe an approach to brain extraction from T1-weighted MR volumes that uses a hierarchy of masks created by different models to form a consensus mask. The algorithm (McStrip) incorporates atlas-based extraction via nonlinear warping, intensity-threshold masking with connectivity constraints, and edge-based masking with morphological operations. Volume and boundary metrics were computed to evaluate the reproducibility and accuracy of McStrip against manual brain extraction on 38 scans from normal and ataxic subjects. McStrip masks were reproducible across six repeat scans of a normal subject and were significantly more accurate than the masks produced by any of the individual algorithmic components. Copyright 2004 Elsevier Inc.

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Year:  2004        PMID: 15219598     DOI: 10.1016/j.neuroimage.2004.03.011

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  16 in total

1.  Skull stripping of neonatal brain MRI: using prior shape information with graph cuts.

Authors:  Dwarikanath Mahapatra
Journal:  J Digit Imaging       Date:  2012-12       Impact factor: 4.056

Review 2.  Methods on Skull Stripping of MRI Head Scan Images-a Review.

Authors:  P Kalavathi; V B Surya Prasath
Journal:  J Digit Imaging       Date:  2016-06       Impact factor: 4.056

3.  Volumetric neuroimage analysis extensions for the MIPAV software package.

Authors:  Pierre-Louis Bazin; Jennifer L Cuzzocreo; Michael A Yassa; William Gandler; Matthew J McAuliffe; Susan S Bassett; Dzung L Pham
Journal:  J Neurosci Methods       Date:  2007-05-29       Impact factor: 2.390

4.  Evaluation of automated brain MR image segmentation and volumetry methods.

Authors:  Frederick Klauschen; Aaron Goldman; Vincent Barra; Andreas Meyer-Lindenberg; Arvid Lundervold
Journal:  Hum Brain Mapp       Date:  2009-04       Impact factor: 5.038

5.  Multiscale segmentation of the skull in MR images for MRI-based attenuation correction of combined MR/PET.

Authors:  Xiaofeng Yang; Baowei Fei
Journal:  J Am Med Inform Assoc       Date:  2013-06-12       Impact factor: 4.497

6.  State-of-the-Art Traditional to the Machine- and Deep-Learning-Based Skull Stripping Techniques, Models, and Algorithms.

Authors:  Anam Fatima; Ahmad Raza Shahid; Basit Raza; Tahir Mustafa Madni; Uzair Iqbal Janjua
Journal:  J Digit Imaging       Date:  2020-12       Impact factor: 4.056

7.  Simple paradigm for extra-cerebral tissue removal: algorithm and analysis.

Authors:  Aaron Carass; Jennifer Cuzzocreo; M Bryan Wheeler; Pierre-Louis Bazin; Susan M Resnick; Jerry L Prince
Journal:  Neuroimage       Date:  2011-03-31       Impact factor: 6.556

8.  LABEL: pediatric brain extraction using learning-based meta-algorithm.

Authors:  Feng Shi; Li Wang; Yakang Dai; John H Gilmore; Weili Lin; Dinggang Shen
Journal:  Neuroimage       Date:  2012-05-24       Impact factor: 6.556

9.  Online resource for validation of brain segmentation methods.

Authors:  David W Shattuck; Gautam Prasad; Mubeena Mirza; Katherine L Narr; Arthur W Toga
Journal:  Neuroimage       Date:  2008-11-25       Impact factor: 6.556

10.  The relationships between the amount of spared tissue, percent signal change, and accuracy in semantic processing in aphasia.

Authors:  Jordyn A Sims; Kushal Kapse; Peter Glynn; Chaleece Sandberg; Yorghos Tripodis; Swathi Kiran
Journal:  Neuropsychologia       Date:  2016-01-13       Impact factor: 3.139

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