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3393 Total Publications

Basal forebrain volume reliably predicts the cortical spread of Alzheimer's degeneraion
Fernandez-Cabello, S, Kronbichler, M, Van Dijk, KRA, Goodman, JA, Spreng, RN, Schmitz, TW and Alzheimer's Dis Neuroimaging, I
2020; Journal Brain; vol. 143; pp. 993-1009;
Small vessel disease more than Alzheimer's disease determines diffusion MRI alterations in memory clinic patients
Finsterwalder, S, Vlegels, N, Gesierich, B, Araque Caballero, M, Weaver, NA, Franzmeier, N, Georgakis, MK, Konieczny, MJ, Koek, HL, Karch, CM, Graff-Radford, NR, Salloway, S, Oh, H, Allegri, RF, Chhatwal, JP, Jessen, F, Düzel, E, Dobisch, L, Metzger, C, Peters, O, Incesoy, EI, Priller, J, Spruth, EJ, Schneider, A, Fließbach, K, Buerger, K, Janowitz, D, Teipel, SJ, Kilimann, I, Laske, C, Buchmann, M, Heneka, MT, Brosseron, F, Spottke, A, Roy, N, Ertl-Wagner, B, Scheffler, K, Seo, SW, Kim, Y, Na, DL, Kim, HJ, Jang, H, Ewers, M, Levin, J, Schmidt, R, Pasternak, O, Dichgans, M, Biessels, GJ and Duering, M
2020; Journal Alzheimers Dement;
Feasibility study of a PET-only amyloid quantification method: a comparison with visual interpretation
Shimokawa, N, Akamatsu, G, Kadosaki, M and Sasaki, M
2020; Journal Ann Nucl Med; vol. 34; no. 9; pp. 629-635;
Effect of apolipoprotein E ε4 allele on the progression of cognitive decline in the early stage of Alzheimer's disease
Suzuki, K, Hirakawa, A, Ihara, R, Iwata, A, Ishii, K, Ikeuchi, T, Sun, CK, Donohue, M and Iwatsubo, T
PMCID:7087431 ; 2020; Journal Alzheimers Dement (N Y); vol. 6; no. 1; pp. e12007;
Performance gains with Compute Unified Device Architecture-enabled eddy current correction for diffusion MRI
Maller, JJ, Grieve, SM, Vogrin, SJ and Welton, T
2020; Journal Neuroreport; vol. 31; no. 10; pp. 746-753;
CSF cutoffs for MCI due to AD depend on APOE epsilon 4 carrier status
Marizzoni, M, Ferrari, C, Babiloni, C, Albani, D, Barkhof, F, Cavaliere, L, Didic, M, Forloni, G, Fusco, F, Galluzzi, S, Hensch, T, Jovicich, J, Marra, C, Molinuevo, JL, Nobili, F, Parnetti, L, Payoux, P, Ranjeva, JP, Ribaldi, F, Rolandi, E, Rossini, PM, Salvatore, M, Soricelli, A, Tsolaki, M, Visser, PJ, Wiltfang, J, Richardson, JC, Bordet, R, Blin, O and Frisoni, GB
2020; Journal Neurobiology of Aging; vol. 89; pp. 55-62;
Application of Deep Learning to Predict Standardized Uptake Value Ratio and Amyloid Status on (18)F-Florbetapir PET Using ADNI Data
Reith, F, Koran, ME, Davidzon, G and Zaharchuk, G
PMCID:7342760 ; 2020; Journal AJNR Am J Neuroradiol; vol. 41; no. 6; pp. 980-986;
Improving brain age prediction models: incorporation of amyloid status in Alzheimer's disease
Ly, M, Yu, GZ, Karim, HT, Muppidi, NR, Mizuno, A, Klunk, WE, Aizenstein, HJ and Alzheimers Dis Neuroimaging, I
2020; Journal Neurobiology of Aging; vol. 87; pp. 44-48;
Associating Multi-Modal Brain Imaging Phenotypes and Genetic Risk Factors via a Dirty Multi-Task Learning Method
Du, L, Liu, F, Liu, KF, Yao, XH, Risacher, SL, Han, JW, Saykin, AJ and Shen, L
2020; Journal Ieee Transactions on Medical Imaging; vol. 39; no. 11; pp. 3416-3428;