Journal ArticleDOI
BrainSuite: An automated cortical surface identification tool
TLDR
A new magnetic resonance (MR) image analysis tool that produces cortical surface representations with spherical topology from MR images of the human brain is described, which is designed to require minimal user interaction to produce cortical representations.About:
This article is published in Medical Image Analysis.The article was published on 2002-06-01. It has received 829 citations till now. The article focuses on the topics: Image processing.read more
Citations
More filters
Journal ArticleDOI
Brainstorm: a user-friendly application for MEG/EEG analysis
TL;DR: Brainstorm as discussed by the authors is a collaborative open-source application dedicated to magnetoencephalography (MEG) and EEG data visualization and processing, with an emphasis on cortical source estimation techniques and their integration with anatomical magnetic resonance imaging (MRI) data.
Journal ArticleDOI
A Hybrid Approach to the Skull Stripping Problem in MRI
Florent Ségonne,Anders M. Dale,Evelina Busa,Maureen Glessner,David H. Salat,Horst K. Hahn,Bruce Fischl +6 more
TL;DR: A novel skull-stripping algorithm based on a hybrid approach that combines watershed algorithms and deformable surface models is presented, resulting in a robust and automated procedure that outperforms other publicly available skullstripping tools.
Journal ArticleDOI
Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer.
Xiao Han,Jorge Jovicich,David H. Salat,Andre van der Kouwe,Brian T. Quinn,Silvester Czanner,Evelina Busa,Jenni Pacheco,Marilyn S. Albert,Marilyn S. Albert,Ronald J. Killiany,Paul Maguire,Diana Rosas,Nikos Makris,Anders M. Dale,Bradford C. Dickerson,Bruce Fischl,Bruce Fischl +17 more
TL;DR: It is demonstrated that MRI-derived cortical thickness measures are highly reliable when MRI instrument and data processing factors are controlled but that it is important to consider these factors in the design of multi-site or longitudinal studies, such as clinical drug trials.
Journal ArticleDOI
Construction of a 3D Probabilistic Atlas of Human Cortical Structures
David W. Shattuck,Mubeena Mirza,Vitria Adisetiyo,Cornelius Hojatkashani,G. Salamon,Katherine L. Narr,Russell A. Poldrack,Robert M. Bilder,Arthur W. Toga +8 more
TL;DR: The construction of a digital brain atlas composed of data from manually delineated MRI data, providing a resource for automated probabilistic labeling of external data types registered into standard spaces, and computed average intensity images and tissue density maps based on the three methods and target spaces.
Journal ArticleDOI
Digimouse: a 3D whole body mouse atlas from CT and cryosection data
TL;DR: A three-dimensional (3D) whole body mouse atlas is constructed from coregistered x-ray CT and cryosection data of a normal nude male mouse and simulations of 3D bioluminescence and PET image reconstruction are included.
References
More filters
Proceedings ArticleDOI
Marching cubes: A high resolution 3D surface construction algorithm
TL;DR: In this paper, a divide-and-conquer approach is used to generate inter-slice connectivity, and then a case table is created to define triangle topology using linear interpolation.
Journal ArticleDOI
Cortical surface-based analysis. I. Segmentation and surface reconstruction
TL;DR: A set of automated procedures for obtaining accurate reconstructions of the cortical surface are described, which have been applied to data from more than 100 subjects, requiring little or no manual intervention.
Journal ArticleDOI
Theory of Edge Detection
David Marr,Ellen C. Hildreth +1 more
TL;DR: The theory of edge detection explains several basic psychophysical findings, and the operation of forming oriented zero-crossing segments from the output of centre-surround ∇2G filters acting on the image forms the basis for a physiological model of simple cells.
Journal ArticleDOI
A nonparametric method for automatic correction of intensity nonuniformity in MRI data
TL;DR: A novel approach to correcting for intensity nonuniformity in magnetic resonance (MR) data is described that achieves high performance without requiring a model of the tissue classes present, and is applied at an early stage in an automated data analysis, before a tissue model is available.