Alzheimer’s Disease Neuroimaging Initiative

5586 Total Publications

Year	Title	Author	Journal
2020	TNF receptors are associated with tau pathology and conversion to Alzheimer's dementia in subjects with mild cognitive impairment	Zhao, A, Li, Y and Deng, Y	Journal Neurosci Lett;
2020	Neuroimaging PheWAS (Phenome-Wide Association Study): A Free Cloud-Computing Platform for Big-Data, Brain-Wide Imaging Association Studies	Zhao, L, Batta, I, Matloff, W, O'Driscoll, C, Hobel, S and Toga, AW	Journal Neuroinformatics;
2020	FCN Based Label Correction for Multi-Atlas Guided Organ Segmentation	Zhu, HC, Adeli, E, Shi, F, Shen, DG and Alzheimers Dis, N	Journal Neuroinformatics;
2020	Limited One-time Sampling Irregularity Map (LOTS-IM) for Automatic Unsupervised Assessment of White Matter Hyperintensities and Multiple Sclerosis Lesions in Structural Brain Magnetic Resonance Images	Rachmadi, MF, Valdes-Hernandez, MD, Li, H, Guerrero, R, Meijboom, R, Wiseman, S, Waldman, A, Zhang, JG, Rueckert, D, Wardlaw, J and Komura, T	Journal Computerized Medical Imaging and Graphics;
2020	Statistical Disease Progression Modeling in Alzheimer Disease	Raket, LL	Journal Front Big Data;
2020	Volumetric Segmentation of Brain Regions From MRI Scans Using 3D Convolutional Neural Networks	Ramzan, F, Khan, MUG, Iqbal, S, Saba, T and Rehman, A	Journal Ieee Access;
2020	Neuroanatomical associations of depression, anxiety and apathy neuropsychiatric symptoms in patients with Alzheimer’s disease	Mohamed Nour, AeA, Jiao, Y, Teng, G-J and Initiative, AsDN	Journal Acta Neurologica Belgica;
2020	Prediction of conversion to Alzheimer's disease using deep survival analysis of MRI images	Nakagawa, T, Ishida, M, Naito, J, Nagai, A, Yamaguchi, S and Onoda, K	Journal Brain Commun;
2020	Comparison of Transfer Learning and Conventional Machine Learning Applied to Structural Brain MRI for the Early Diagnosis and Prognosis of Alzheimer's Disease	Nanni, L, Interlenghi, M, Brahnam, S, Salvatore, C, Papa, S, Nemni, R and Castiglioni, I	Journal Front Neurol;
2020	Selection of the optimal intensity normalization region for FDG-PET studies of normal aging and Alzheimer's disease	Nugent, S, Croteau, E, Potvin, O, Castellano, CA, Dieumegarde, L, Cunnane, SC and Duchesne, S	Journal Scientific Reports;