Automatic hippocampus segmentation of 7.0Tesla MR images by combining multiple atlases and auto-context models
暂无分享,去创建一个
Wei Li | Dinggang Shen | Guorong Wu | Li Wang | Zang-Hee Cho | Minjeong Kim | Young-Don Son | Wei Li | D. Shen | Guorong Wu | Z. Cho | Minjeong Kim | Li Wang | Y. Son
[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] Torsten Rohlfing,et al. Multi-classifier framework for atlas-based image segmentation , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[3] D. Louis Collins,et al. Automatic 3‐D model‐based neuroanatomical segmentation , 1995 .
[4] Robert M. Haralick,et al. Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..
[5] J. Ehrhardt,et al. Measurement of brain structures with artificial neural networks: two- and three-dimensional applications. , 1999, Radiology.
[6] Tony F. Chan,et al. Active contours without edges , 2001, IEEE Trans. Image Process..
[7] Alexander Hammers,et al. Automatic segmentation of the hippocampus and the amygdala driven by hybrid constraints: Method and validation , 2009, NeuroImage.
[8] Daniel Rueckert,et al. Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy , 2009, NeuroImage.
[9] Paul A. Yushkevich,et al. Deformable M-Reps for 3D Medical Image Segmentation , 2003, International Journal of Computer Vision.
[10] C. Jack,et al. Alzheimer's Disease Neuroimaging Initiative , 2008 .
[11] Wiro J. Niessen,et al. Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts , 2008, NeuroImage.
[12] Brian B. Avants,et al. A High-Resolution Computational Atlas of the Human Hippocampus from Postmortem Magnetic Resonance Imaging at 9 . 4 Tesla , 2008 .
[13] D. Louis Collins,et al. Appearance-based modeling for segmentation of hippocampus and amygdala using multi-contrast MR imaging , 2011, NeuroImage.
[14] Daniel Rueckert,et al. Automatic anatomical brain MRI segmentation combining label propagation and decision fusion , 2006, NeuroImage.
[15] N C Andreasen,et al. A new method for the in vivo volumetric measurement of the human hippocampus with high neuroanatomical accuracy , 2000, Hippocampus.
[16] Nick C Fox,et al. The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods , 2008, Journal of magnetic resonance imaging : JMRI.
[17] Brian B. Avants,et al. The optimal template effect in hippocampus studies of diseased populations , 2010, NeuroImage.
[18] Jyrki Lötjönen,et al. Fast and robust extraction of hippocampus from MR images for diagnostics of Alzheimer's disease , 2011, NeuroImage.
[19] Nicolas Cherbuin,et al. Optimal weights for local multi-atlas fusion using supervised learning and dynamic information (SuperDyn): Validation on hippocampus segmentation , 2011, NeuroImage.
[20] Robert F. Murphy,et al. Application of temporal texture features to automated analysis of protein subcellular locations in time series fluorescence microscope images , 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..
[21] A. Dale,et al. Whole Brain Segmentation Automated Labeling of Neuroanatomical Structures in the Human Brain , 2002, Neuron.
[22] Michael Weiner,et al. and the Alzheimer’s Disease Neuroimaging Initiative* , 2007 .
[23] Carlos Ortiz-de-Solorzano,et al. Combination Strategies in Multi-Atlas Image Segmentation: Application to Brain MR Data , 2009, IEEE Transactions on Medical Imaging.
[24] Timothy F. Cootes,et al. A Unified Information-Theoretic Approach to Groupwise Non-rigid Registration and Model Building , 2005, IPMI.
[25] Dae-Shik Kim,et al. Quantitative analysis of the hippocampus using images obtained from 7.0 T MRI , 2010, NeuroImage.
[26] Juha Koikkalainen,et al. Fast and robust multi-atlas segmentation of brain magnetic resonance images , 2010, NeuroImage.
[27] Max A. Viergever,et al. Label Fusion in Atlas-Based Segmentation Using a Selective and Iterative Method for Performance Level Estimation (SIMPLE) , 2010, IEEE Transactions on Medical Imaging.
[28] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[29] Michaël Sdika,et al. Combining atlas based segmentation and intensity classification with nearest neighbor transform and accuracy weighted vote , 2010, Medical Image Anal..
[30] Juan Zhou,et al. Segmentation of subcortical brain structures using fuzzy templates , 2005, NeuroImage.
[31] Liana G. Apostolova,et al. Automatic Subcortical Segmentation Using a Contextual Model , 2008, MICCAI.
[32] Paul A. Yushkevich,et al. Multiscale deformable model segmentation and statistical shape analysis using medial descriptions , 2002, IEEE Transactions on Medical Imaging.
[33] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.
[34] D. Louis Collins,et al. Patch-based segmentation using expert priors: Application to hippocampus and ventricle segmentation , 2011, NeuroImage.
[35] Stephanie Powell,et al. Registration and machine learning-based automated segmentation of subcortical and cerebellar brain structures , 2008, NeuroImage.
[36] 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.
[37] S. Resnick,et al. Measuring Size and Shape of the Hippocampus in MR Images Using a Deformable Shape Model , 2002, NeuroImage.
[38] L G Nyúl,et al. On standardizing the MR image intensity scale , 1999, Magnetic resonance in medicine.
[39] Liana G. Apostolova,et al. Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer's Disease Through Automated Hippocampal Segmentation , 2010, IEEE Transactions on Medical Imaging.
[40] Brian B. Avants,et al. A high-resolution computational atlas of the human hippocampus from postmortem magnetic resonance imaging at 9.4 T , 2009, NeuroImage.
[41] Alan C. Evans,et al. A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.
[42] Michael Weiner,et al. Nearly automatic segmentation of hippocampal subfields in in vivo focal T2-weighted MRI , 2010, NeuroImage.
[43] Ali R. Khan,et al. FreeSurfer-initiated fully-automated subcortical brain segmentation in MRI using Large Deformation Diffeomorphic Metric Mapping , 2008, NeuroImage.
[44] Jae-Yong Han,et al. New brain atlas—Mapping the human brain in vivo with 7.0 T MRI and comparison with postmortem histology: Will these images change modern medicine? , 2008 .
[45] Paul A. Viola,et al. Robust Real-Time Face Detection , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[46] Zhuowen Tu,et al. Auto-Context and Its Application to High-Level Vision Tasks and 3D Brain Image Segmentation , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[47] Brian B. Avants,et al. A learning-based wrapper method to correct systematic errors in automatic image segmentation: Consistently improved performance in hippocampus, cortex and brain segmentation , 2011, NeuroImage.
[48] Cameron S. Carter,et al. Optimum template selection for atlas-based segmentation , 2007, NeuroImage.
[49] C R Jack,et al. MRI-based hippocampal volumetrics: data acquisition, normal ranges, and optimal protocol. , 1995, Magnetic resonance imaging.
[50] R. Kikinis,et al. An Automated Registration Algorithm for Measuring MRI Subcortical Brain Structures , 1997, NeuroImage.