On the estimation and correction of bias in local atrophy estimations using example atrophy simulations
Tài liệu tham khảo
Lanz, 2007, Brain atrophy and cognitive impairment in multiple sclerosis: a review, J Neurol, 254, 43
Chan, 2001, Rates of global and regional cerebral atrophy in AD and frontotemporal dementia, Neurology, 57, 1756, 10.1212/WNL.57.10.1756
Freeborough, 1997, The boundary shift integral: an accurate and robust measure of cerebral volume changes from registered repeat MRI, IEEE Trans Med Imag, 16, 623, 10.1109/42.640753
Smith, 2002, Accurate, robust and automated longitudinal and cross-sectional brain change analysis, NeuroImage, 17, 479, 10.1006/nimg.2002.1040
Pieperhoff, 2008, Detection of structural changes of the human brain in longitudinally acquired MR images by deformation field morphometry: methodological analysis, validation and application, NeuroImage, 43, 269, 10.1016/j.neuroimage.2008.07.031
Sharma, 2010, Evaluation of brain atrophy estimation algorithms using simulated ground-truth data, Med Image Anal, 14, 373, 10.1016/j.media.2010.02.002
Smith, 2007, Longitudinal and cross-sectional analysis of atrophy in Alzheimer's disease: cross validation of BSI, SIENA and SIENAX, NeuroImage, 36, 1200, 10.1016/j.neuroimage.2007.04.035
Karacali, 2006, Simulation of tissue atrophy using a topology preserving transformation model, IEEE Trans Med Imag, 25, 649, 10.1109/TMI.2006.873221
Camara, 2008, Accuracy assessment of global and local atrophy measurement techniques with realistic simulated longitudinal Alzheimer's disease images, NeuroImage, 42, 696, 10.1016/j.neuroimage.2008.04.259
Rohlfing, 2006, Transformation model and constraints cause bias in statistics on deformation fields, 207
Lee, 2008, Physically-based validation of deformable medical image registration, 830
Kybic, 2010, Bootstrap resampling for image registration uncertainty estimation without ground truth, IEEE Trans Image Process, 19, 64, 10.1109/TIP.2009.2030955
Hub, 2009, A stochastic approach to estimate the uncertainty involved in B-spline image registration, IEEE Trans Med Imag, 28, 1708, 10.1109/TMI.2009.2021063
Jalobeanu, 2008, Inferring deformation fields from multidate satellite images, Int Geosci Remote Se (Boston MA, USA), 2, 962
Richard, 2007, Metropolis-hasting techniques for finite-element-based registration, 1
Toews, 2009, Bayesian registration via local image regions: information, selection and marginalization, 435
Risholm, 2010, Bayesian estimation of deformation and elastic parameters in non-rigid registration, Lect Notes Comput Sci, 6204, 104, 10.1007/978-3-642-14366-3_10
Risholm, 2010, Summarizing and visualizing registration uncertainty in non-rigid registration, Med Image Comput Comput Assist Interv, 13, 554
Fox, 2011, Algorithms, atrophy and Alzheimer's disease: cautionary tales for clinical trials, NeuroImage, 57, 15, 10.1016/j.neuroimage.2011.01.077
Leow, 2007, Statistical properties of Jacobian maps and the realization of unbiased large-deformation nonlinear image registration, IEEE Trans Med Imag, 26, 822, 10.1109/TMI.2007.892646
Yanovsky, 2009, Comparing registration methods for mapping brain change using tensor-based morphometry, Med Image Anal, 13, 679, 10.1016/j.media.2009.06.002
Yushkevich, 2010, Bias in estimation of hippocampal atrophy using deformation-based morphometry arises from asymmetric global normalization: an illustration in ADNI 3 T MRI data, NeuroImage, 50, 434, 10.1016/j.neuroimage.2009.12.007
Hua, 2011, Accurate measurement of brain changes in longitudinal MRI scans using tensor-based morphometry, NeuroImage, 57, 5, 10.1016/j.neuroimage.2011.01.079
Avants, 2008, Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain, Med Image Anal, 12, 26, 10.1016/j.media.2007.06.004
Wang, 2011, Surface-based TBM boosts power to detect disease effects on the brain: an N=804 ADNI study, NeuroImage, 56, 1993, 10.1016/j.neuroimage.2011.03.040
Noblet, 2005, 3D deformable image registration: a topology preservation scheme based on hierarchical deformation models and interval analysis optimization, IEEE Trans Image Process, 14, 553, 10.1109/TIP.2005.846026
Vemuri, 2003, Image registration via level-set motion: applications to atlas-based segmentation, Med Image Anal, 7, 1, 10.1016/S1361-8415(02)00063-4
Gudbjartsson, 1995, The Rician distribution of noisy MRI data, Magnet Reson Med, 34, 910, 10.1002/mrm.1910340618
Aja-Fernandez, 2008, Noise and signal estimation in magnitude MRI and Rician distributed images: a LMMSE approach, IEEE Trans Image Process, 17, 1383, 10.1109/TIP.2008.925382
Klein, 2009, Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration, NeuroImage, 46, 786, 10.1016/j.neuroimage.2008.12.037
Anderson, 2010, Hippocampal atrophy in relapsing-remitting and primary progressive MS: a comparative study, Mult Scler, 16, 1083, 10.1177/1352458510374893
Lewis, 2004, Correction of differential intensity inhomogeneity in longitudinal MR images, NeuroImage, 23, 75, 10.1016/j.neuroimage.2004.04.030
Cocosco, 1997, BrainWeb: online interface to a 3D MRI simulated brain database, NeuroImage, 5, S425