Filters








2,012 Hits in 10.1 sec

Mathematical Methods in Biomedical Image Analysis (MMBIA 2007)

2007 2007 IEEE 11th International Conference on Computer Vision  
Spencer, James Duncan [PDF paper] ORAL 4: BRAIN: THE CORTEX "Measuring Cortical Thickness Using An Image Domain Local Surface Model And Topology Preserving Segmentation" Sandhitsu Das, Brian Avants  ...  Ellen Grant, Bruce Fischl, Polina Golland "Detecting Cortical Surface Regions in Structural MR Data" Biswajit Bose, John Fisher, Bruce Fischl, Oliver Hinds, Eric Grimson "3D Topology Preserving Flows  ... 
doi:10.1109/iccv.2007.4408823 fatcat:dcdpjaymqve75lxshxmbhif24m

Automated 3-D Extraction of Inner and Outer Surfaces of Cerebral Cortex from MRI

David MacDonald, Noor Kabani, David Avis, Alan C. Evans
2000 NeuroImage  
These results are shown to corroborate published postmortem and in vivo measurements of cortical thickness.  ...  The collection of surfaces has been used to create a spatial map of the mean and standard deviation for the location and the thickness of cortical gray matter.  ...  Many conventional methods use an image term based on the image value at a point on the deforming surface, implicitly using the local gradient of the image to "push" the surface toward the correct edge.  ... 
doi:10.1006/nimg.1999.0534 pmid:10944416 fatcat:zswt6dhamzbo5aclbhluiopm2m

Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification

June Sic Kim, Vivek Singh, Jun Ki Lee, Jason Lerch, Yasser Ad-Dab'bagh, David MacDonald, Jong Min Lee, Sun I. Kim, Alan C. Evans
2005 NeuroImage  
The Anatomic Segmentation using Proximity (ASP) algorithm, previously developed by our group, provides a topology-preserving cortical surface deformation method that has been extensively used for the aforementioned  ...  However, constraints in the algorithm to ensure topology preservation occasionally produce incorrect thickness measurements due to a restriction in the range of allowable distances between the gray and  ...  Acknowledgments This work was supported by the Post-doctoral Fellowship Program of Korea Science and Engineering Foundation (KOSEF).  ... 
doi:10.1016/j.neuroimage.2005.03.036 pmid:15896981 fatcat:vtohlijhoja3plmlwwdku4eqii

Computational neuroanatomy of baby brains: A review

Gang Li, Li Wang, Pew-Thian Yap, Fan Wang, Zhengwang Wu, Yu Meng, Pei Dong, Jaeil Kim, Feng Shi, Islem Rekik, Weili Lin, Dinggang Shen
2018 NeuroImage  
The first postnatal years are an exceptionally dynamic and critical period of structural, functional and connectivity development of the human brain.  ...  comparison with adult brain MR images.  ...  Acknowledgements This work was partially supported by NIH grants (MH100217, MH107815, MH108914, MH109773, MH110274 and NS093842).  ... 
doi:10.1016/j.neuroimage.2018.03.042 pmid:29574033 pmcid:PMC6150852 fatcat:w2o27wt5afhktd7zoophmhnmi4

CRUISE: Cortical reconstruction using implicit surface evolution

Xiao Han, Dzung L. Pham, Duygu Tosun, Maryam E. Rettmann, Chenyang Xu, Jerry L. Prince
2004 NeuroImage  
The method combines a fuzzy tissue classification method, an efficient topology correction algorithm, and a topology-preserving geometric deformable surface model (TGDM).  ...  A successful segmentation method must be robust to various imaging artifacts and produce anatomically meaningful and consistent cortical representations.  ...  Susan Resnick for providing the BLSA data and for discussions on validation studies. We would also like to thank Ms. Daphne Yu and Mr.  ... 
doi:10.1016/j.neuroimage.2004.06.043 pmid:15528100 fatcat:hv3wfe2i4jcljbcgj2435oawpy

Registration based cortical thickness measurement

Sandhitsu R. Das, Brian B. Avants, Murray Grossman, James C. Gee
2009 NeuroImage  
Cortical thickness is an important biomarker for image-based studies of the brain.  ...  A diffeomorphic registration based cortical thickness (DiReCT) measure is introduced where a continuous one-to-one correspondence between the gray matter-white matter interface and the estimated gray matter-cerebrospinal  ...  Acknowledgment This work was supported in part by NIH grants EB006266, NS045839, DA022807, DA14129, and HD046159.  ... 
doi:10.1016/j.neuroimage.2008.12.016 pmid:19150502 pmcid:PMC2836782 fatcat:uqaumyfpxjeqzo6amq3jy2ag6a

Cortical surface mapping using topology correction, partial flattening and 3D shape context-based non-rigid registration for use in quantifying atrophy in Alzheimer's disease

Oscar Acosta, Jurgen Fripp, Vincent Doré, Pierrick Bourgeat, Jean-Marie Favreau, Gaël Chételat, Andrea Rueda, Victor L. Villemagne, Cassandra Szoeke, David Ames, Kathryn A. Ellis, Ralph N. Martins (+8 others)
2012 Journal of Neuroscience Methods  
Partial inflation and non--rigid registration of cortical surfaces to a common space using shape context are then performed.  ...  The brain is first segmented into the three main tissues: white matter, gray matter and cerebrospinal fluid, after CTE is computed, a topology corrected mesh is generated.  ...  In (Cardoso et al. 2011 ) an explicit model of partial volume classes is introduced within the segmentation step and a locally varying MRF--based model is used to locally modify the priors for enhancement  ... 
doi:10.1016/j.jneumeth.2011.12.011 pmid:22226742 fatcat:vfdtx6kzxfb5hkpv6uad23al6u

Cortical surface segmentation and mapping

Duygu Tosun, Maryam E. Rettmann, Xiao Han, Xiaodong Tao, Chenyang Xu, Susan M. Resnick, Dzung L. Pham, Jerry L. Prince
2004 NeuroImage  
Segmentation and mapping of the human cerebral cortex from magnetic resonance (MR) images plays an important role in neuroscience and medicine.  ...  This paper describes a comprehensive approach for cortical reconstruction, flattening, and sulcal segmentation.  ...  Noor Kabani for providing the hand-labeled atlas data and Kirsten Behnke for assistance with the atlas data. This work was supported in part by NIH/NINDS Grant R01NS37747.  ... 
doi:10.1016/j.neuroimage.2004.07.042 pmid:15501080 pmcid:PMC4587756 fatcat:5poegzjszvhnpfq7zha2haka24

Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination

Won Hwa Kim, Deepti Pachauri, Charles Hatt, Moo K. Chung, Sterling C. Johnson, Vikas Singh
2012 Neural Information Processing Systems  
In contrast to hypothesis tests on point-wise measurements, in this paper, we make the case for performing statistical analysis on multi-scale shape descriptors that characterize the local topological  ...  Hypothesis testing on signals defined on surfaces (such as the cortical surface) is a fundamental component of a variety of studies in Neuroscience.  ...  Acknowledgments This research was supported by funding from NIH R01AG040396, NIH R01AG021155, NSF RI 1116584, the Wisconsin Partnership Proposal, UW ADRC, and UW ICTR (1UL1RR025011).  ... 
dblp:conf/nips/KimPHCJS12 fatcat:6gn5yxvr5nejtdgblgpgd4cueq

Enhanced cortical thickness measurements for rodent brains via Lagrangian-based RK4 streamline computation

Joohwi Lee, Sun Hyung Kim, Ipek Oguz, Martin Styner, Martin A. Styner, Elsa D. Angelini
2016 Medical Imaging 2016: Image Processing  
Based on a previously proposed cortical thickness measurement pipeline for rodent brain analysis, 1 we present an enhanced cortical thickness pipeline in terms of accuracy and anatomical consistency.  ...  The cortical thickness of the mammalian brain is an important morphological characteristic that can be used to investigate and observe the brain's developmental changes that might be caused by biologically  ...  However, surface-based cortical thickness methods should employ methods to preserve the correct topology between two surfaces, such as smoothness and self-intersection constraints or Laplacian functions  ... 
doi:10.1117/12.2216420 pmid:27065047 pmcid:PMC4825173 dblp:conf/miip/LeeKOS16 fatcat:6r7g3c6bp5faffom2gwwym45se

Reconstruction of central cortical surface from brain MRI images: Method and application

Tianming Liu, Jingxin Nie, Ashley Tarokh, Lei Guo, Stephen T.C. Wong
2008 NeuroImage  
Both simulated brain cortexes and real brain images are used to evaluate this approach.  ...  In this paper, we propose a novel method based on an elastic transform vector field to drive a deformable model for the reconstruction of the central cortical surface.  ...  An advantage of the parametric surface model is that the topology of the final surface is identical to that of the initial one, provided that the deformation is topology-preserving MacDonald et al., 2000  ... 
doi:10.1016/j.neuroimage.2007.12.027 pmid:18289879 pmcid:PMC2505350 fatcat:heqjlle6gbcahcwfhrxhkqmdhe

FreeSurfer

Bruce Fischl
2012 NeuroImage  
It has evolved from a package primarily aimed at generating surface representations of the cerebral cortex into one that automatically creates models of most macroscopically visible structures in the human  ...  brain given any reasonable T1-weighted input image.  ...  for Biomedical Imaging and Bioengineering (R01EB006758), the National Institute on Aging (AG022381), the National Center for Alternative Medicine (RC1 AT005728-01), the National Institute for Neurological  ... 
doi:10.1016/j.neuroimage.2012.01.021 pmid:22248573 pmcid:PMC3685476 fatcat:nkxyxri74vgvzlnorxduawgsca

Brain Surface Conformal Parameterization Using Riemann Surface Structure

Yalin Wang, Lok Ming Lui, Xianfeng Gu, Kiralee M. Hayashi, Tony F. Chan, Arthur W. Toga, Paul M. Thompson, Shing-Tung Yau
2007 IEEE Transactions on Medical Imaging  
In medical imaging, parameterized 3-D surface models are useful for anatomical modeling and visualization, statistical comparisons of anatomy, and surface-based registration and signal processing.  ...  Finally, we present an automatic sulcal landmark location algorithm by solving PDEs on cortical surfaces.  ...  imaging parameters localized on anatomical surfaces.  ... 
doi:10.1109/tmi.2007.895464 pmid:17679336 pmcid:PMC3197830 fatcat:qe6uqvdavfcatnkv6acmkvjkky

Human cerebral cortex: A system for the integration of volume- and surface-based representations

Nikos Makris, Jonathan Kaiser, Christian Haselgrove, Larry J. Seidman, Joseph Biederman, Denise Boriel, Eve M. Valera, George M. Papadimitriou, Bruce Fischl, Verne S. Caviness, David N. Kennedy
2006 NeuroImage  
program to generate a cortical ribbon of the cerebrum and perform cortical topographic measurements (including thickness, surface area and curvature) in individual subjects as well as in subject populations  ...  We describe an MRI-based system for topological analysis followed by measurements of topographic features for the human cerebral cortex that takes as its starting point volumetric segmentation data.  ...  A third domain of use will be in topological measurements of cortical thickness, surface area, volume, curvature, and folding index of regional anatomy providing comprehensive and complete information  ... 
doi:10.1016/j.neuroimage.2006.04.220 pmid:16920366 fatcat:eoqoq4sw3rghdlrs7n7vxtlzbm

Proximity constraints in deformable models for cortical surface identification [chapter]

David MacDonald, David Avis, Alan C. Evans
1998 Lecture Notes in Computer Science  
A large number of individual surfaces (N=151) are created and a spatial map of the mean and standard deviation of the cerebral cortex and the thickness of cortical gray matter are generated.  ...  These two features are used advantageously to automatically identify the total surface of the cerebral cortical gray matter from normal human MR images, accurately locating the depths of the sulci even  ...  Cortical Thickness Map The thickness of the gray matter can be measured at any point on an individual cortical surface, using the two deformed surfaces, and averaged over the entire set of surfaces, shown  ... 
doi:10.1007/bfb0056251 fatcat:dysjwzplzndnjnav7lf36c5vwm
« Previous Showing results 1 — 15 out of 2,012 results