A Novel Approach for the Prediction of Conversion from Mild Cognitive Impairment to Alzheimer's disease using MRI Images

The main objective of our research is to introduce an approach that uses noninvasive MRI images to predict the conversion from mild cognitive impairment to Alzheimer's disease at an ea ...

[1]  C. Jack,et al.  11C PiB and structural MRI provide complementary information in imaging of Alzheimer's disease and amnestic mild cognitive impairment. , 2008, Brain : a journal of neurology.

[2]  Chunshui Yu,et al.  3D texture analysis on MRI images of Alzheimer’s disease , 2011, Brain Imaging and Behavior.

[3]  Nick C Fox,et al.  Automatic classification of MR scans in Alzheimer's disease. , 2008, Brain : a journal of neurology.

[4]  Daoqiang Zhang,et al.  Multimodal classification of Alzheimer's disease and mild cognitive impairment , 2011, NeuroImage.

[5]  Heikki Huttunen,et al.  Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects , 2015, NeuroImage.

[6]  Yudong Zhang,et al.  Classification of Alzheimer Disease Based on Structural Magnetic Resonance Imaging by Kernel Support Vector Machine Decision Tree , 2014 .

[7]  Li Shen,et al.  Baseline MRI Predictors of Conversion from MCI to Probable AD in the ADNI Cohort , 2009, Current Alzheimer research.

[8]  M. Filippi,et al.  The contribution of voxel-based morphometry in staging patients with mild cognitive impairment , 2006, Neurology.

[9]  Christos Davatzikos,et al.  Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: Results from ADNI , 2009, NeuroImage.

[10]  Yudong Zhang,et al.  Detection of Alzheimer's disease and mild cognitive impairment based on structural volumetric MR images using 3D-DWT and WTA-KSVM trained by PSOTVAC , 2015, Biomed. Signal Process. Control..

[11]  Karl J. Friston,et al.  Automatic Differentiation of Anatomical Patterns in the Human Brain: Validation with Studies of Degenerative Dementias , 2002, NeuroImage.

[12]  R. Leahy,et al.  Magnetic Resonance Image Tissue Classification Using a Partial Volume Model , 2001, NeuroImage.

[13]  R. Petersen Mild cognitive impairment as a diagnostic entity , 2004, Journal of internal medicine.

[14]  R. Petersen,et al.  Cerebrospinal fluid biomarker signature in Alzheimer's disease neuroimaging initiative subjects , 2009, Annals of neurology.

[15]  Eini Niskanen,et al.  Voxel-based morphometry to detect brain atrophy in progressive mild cognitive impairment , 2007, NeuroImage.

[16]  Francisco Jesús Martínez-Murcia,et al.  LVQ-SVM based CAD tool applied to structural MRI for the diagnosis of the Alzheimer's disease , 2013, Pattern Recognit. Lett..

[17]  Karl J. Friston,et al.  Voxel-based morphometry of the human brain: Methods and applications , 2005 .

[18]  Lei Wang,et al.  Fully‐automated, multi‐stage hippocampus mapping in very mild Alzheimer disease , 2009, Hippocampus.

[19]  Roman Filipovych,et al.  Semi-supervised pattern classification of medical images: Application to mild cognitive impairment (MCI) , 2011, NeuroImage.

[20]  X. Wu,et al.  Individual patient diagnosis of AD and FTD via high-dimensional pattern classification of MRI , 2008, NeuroImage.

[21]  S. Resnick,et al.  Detection of prodromal Alzheimer's disease via pattern classification of magnetic resonance imaging , 2008, Neurobiology of Aging.

[22]  Takashi Asada,et al.  Voxel-based morphometry to discriminate early Alzheimer's disease from controls , 2005, Neuroscience Letters.

[23]  Brigitte Landeau,et al.  Using voxel-based morphometry to map the structural changes associated with rapid conversion in MCI: A longitudinal MRI study , 2005, NeuroImage.

[24]  Kathryn Ziegler-Graham,et al.  Forecasting the global burden of Alzheimer’s disease , 2007, Alzheimer's & Dementia.

[25]  R. Chapman,et al.  Please Scroll down for Article Journal of Clinical and Experimental Neuropsychology Predicting Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using Neuropsychological Tests and Multivariate Methods , 2022 .

[26]  S. Resnick,et al.  Alzheimer's Disease Risk Assessment Using Large-Scale Machine Learning Methods , 2013, PloS one.

[27]  Rozi Mahmud,et al.  Boosting diagnosis accuracy of Alzheimer's disease using high dimensional recognition of longitudinal brain atrophy patterns , 2015, Behavioural Brain Research.

[28]  H. Benali,et al.  Discrimination between Alzheimer disease, mild cognitive impairment, and normal aging by using automated segmentation of the hippocampus. , 2008, Radiology.

[29]  Stephen M. Smith,et al.  SUSAN—A New Approach to Low Level Image Processing , 1997, International Journal of Computer Vision.

[30]  et al.,et al.  Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline , 2008, NeuroImage.

[31]  Clifford R Jack,et al.  Neuroimaging in Alzheimer disease: an evidence-based review. , 2003, Neuroimaging clinics of North America.

[32]  Xiaoying Wu,et al.  Structural and functional biomarkers of prodromal Alzheimer's disease: A high-dimensional pattern classification study , 2008, NeuroImage.

[33]  Marie Chupin,et al.  Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging , 2009, NeuroImage.

[34]  Nick C Fox,et al.  Brain imaging in Alzheimer disease. , 2012, Cold Spring Harbor perspectives in medicine.

[35]  Juan Manuel Górriz,et al.  Early diagnosis of Alzheimer's disease based on partial least squares, principal component analysis and support vector machine using segmented MRI images , 2015, Neurocomputing.

[36]  Karl J. Friston,et al.  Voxel-Based Morphometry—The Methods , 2000, NeuroImage.

[37]  H. Benali,et al.  Fully automatic hippocampus segmentation and classification in Alzheimer's disease and mild cognitive impairment applied on data from ADNI , 2009, Hippocampus.

[38]  J. Baron,et al.  Mapping gray matter loss with voxel-based morphometry in mild cognitive impairment , 2002, Neuroreport.

[39]  Kun Hu,et al.  Multi-scale features extraction from baseline structure MRI for MCI patient classification and AD early diagnosis , 2016, Neurocomputing.