The Alzheimer’s disease neuroimaging initiative (ADNI): MRI methods

Cited by (1,039)

Items 801–900 of 1,039

1. Frequency-dependent changes in fractional amplitude of low-frequency oscillations in Alzheimer’s disease: a resting-state fMRI study
   Yang Liu, Yan Yan, Yuxia Li, Xiaochen Hu, Jie Lu, Piu Chan, Tianyi Yan, Ying Han · 2019 · Brain Imaging and Behavior
2. Anatomical Attention Guided Deep Networks for ROI Segmentation of Brain MR Images
   Liang Sun, Wei Shao, Daoqiang Zhang, Mingxia Liu · 2019 · IEEE Transactions on Medical Imaging
3. A peripheral neutrophil-related inflammatory factor predicts a decline in executive function in mild Alzheimer’s disease
   Alzheimer’s Disease Neuroimaging Initiative, Kritleen Kaur Bawa, Saffire Hanna Krance, Nathan Herrmann, Hugo Cogo‐Moreira, Michael Ouk, Di Yu, Che‐Yuan Wu, Sandra E. Black, Krista L. Lanctôt et al. · 2020 · Journal of Neuroinflammation
4. Volumetric Segmentation of Brain Regions From MRI Scans Using 3D Convolutional Neural Networks
   Farheen Ramzan, Muhammad Usman Ghani Khan, Sajid Iqbal, Tanzila Saba, Amjad Ur Rehman · 2020 · IEEE Access
5. Deep recurrent model for individualized prediction of Alzheimer’s disease progression
   Wonsik Jung, Eunji Jun, Heung‐Il Suk · 2021 · NeuroImage
6. Plasma pTau181 predicts cortical brain atrophy in aging and Alzheimer’s disease
   Alzheimer’s Disease Neuroimaging Initiative, Cécile Tissot, Andréa Lessa Benedet, Joseph Therriault, Tharick Ali Pascoal, Firoza Zubeida Lussier, Paramita Saha‐Chaudhuri, Mira Chamoun, Mélissa Savard, Sulantha Sanjeewa Mathotaarachchi et al. · 2021 · Alzheimer s Research & Therapy
7. Alzheimer’s disease diagnosis via multimodal feature fusion
   Yue Tu, Shukuan Lin, Jianzhong Qiao, Yilin Zhuang, Peng Zhang · 2022 · Computers in Biology and Medicine
8. Deep-Learning-Based Diagnosis and Prognosis of Alzheimer’s Disease: A Comprehensive Review
   Rahul Sharma, Tripti Goel, M. Tanveer, Chin‐Teng Lin, R. Murugan · 2023 · IEEE Transactions on Cognitive and Developmental Systems
9. Reductions of Thalamic Volume and Regional Shape Changes in the Vegetative and the Minimally Conscious States
   Davinia Fernández‐Espejo, Carme Junqué, Montserrat Bernabeu, Teresa Roig-Rovira, Pere Vendrell, J M Mercader · 2010 · Journal of Neurotrauma
10. Comparison of Imaging Biomarkers in the Alzheimer Disease Neuroimaging Initiative and the Mayo Clinic Study of Aging
    Jennifer Louise Whitwell · 2012 · Archives of Neurology
11. Defining and labeling disease‐modifying treatments for Alzheimer's disease
    Jeffrey L. Cummings · 2009 · Alzheimer s & Dementia
12. Disease classification with hippocampal shape invariants
    Boris A. Gutman, Yalin Wang, Jonathan H. Morra, Arthur W. Toga, Paul M. Thompson · 2009 · Hippocampus
13. Multi-Hypergraph Learning for Incomplete Multimodality Data
    Mingxia Liu, Yue Gao, Pew‐Thian Yap, Dinggang G. Shen · 2017 · IEEE Journal of Biomedical and Health Informatics
14. Genome‐wide association study of Alzheimer's disease endophenotypes at prediagnosis stages
    Chung, Jaeyoon, Wang, Xulong, Maruyama, Toru, Ma, Yiyi, Zhang, Xiaoling, Mez, Jesse, Sherva, Richard, Takeyama, Haruko, The Alzheimer's Disease Neuroimaging Initiative, Lunetta, Kathryn L. et al. · 2018 · Alzheimer's & Dementia
15. Lipids in Amyloid-β Processing, Aggregation, and Toxicity
    Isabel Morgado, Megan Garvey · 2015 · Advances in experimental medicine and biology
16. Spatial and Anatomical Regularization of SVM: A General Framework for Neuroimaging Data
    Rémi Cuingnet, Joan Glaunès, Marie Chupin A, Habib Benali, Olivier Colliot · 2012 · IEEE Transactions on Pattern Analysis and Machine Intelligence
17. Use of Electronic Health Data for Disease Prediction: A Comprehensive Literature Review
    Md Ekramul Hossain, Arif M. Khan, Mohammad Ali Moni, Shahadat Uddin · 2019 · IEEE Transactions on Computational Biology and Bioinformatics
18. Dexmedetomidine Provides Protection Against Hippocampal Neuron Apoptosis and Cognitive Impairment in Mice with Alzheimer’s Disease by Mediating the miR-129/YAP1/JAG1 Axis
    Weiying Sun, Jun Zhao, Chunzhi Li · 2020 · Molecular Neurobiology
19. Genome-wide association study of Alzheimer’s disease CSF biomarkers in the EMIF-AD Multimodal Biomarker Discovery dataset
    Shengjun Hong, Dmitry Prokopenko, Valerija Dobričić, Fabian Kilpert, Isabelle Bos, Stephanie J. B. Vos, Betty Marije Tijms, Ulf Andréasson, Kaj Blennow, Rik R. Vandenberghe et al. · 2020 · Translational Psychiatry
20. A hierarchical attention-based multimodal fusion framework for predicting the progression of Alzheimer’s disease
    Peixin Lu, Lianting Hu, Alexis Mitelpunkt, Surbhi Bhatnagar, Long Jason Lu, Huiying Liang · 2023 · Biomedical Signal Processing and Control
21. Distribution of Pathology in Frontal Variant Alzheimer's Disease
    Richard C. Blennerhassett, Patricia Lillo, Glenda Margaret Halliday, John R. Hodges, Jillian J. Kril · 2014 · Journal of Alzheimer s Disease
22. Genetic influence of apolipoprotein E4 genotype on hippocampal morphometry: An N = 725 surface‐based Alzheimer's disease neuroimaging initiative study
    Jie Shi, Natasha Leporé, Boris A. Gutman, Paul M. Thompson, Leslie C. Baxter, Richard J. Caselli, Yalin Wang, Alzheimer’s Disease Neuroimaging Initiative · 2014 · Human Brain Mapping
23. Dissecting the Gene Dose-Effects of the APOE ε4 and ε2 Alleles on Hippocampal Volumes in Aging and Alzheimer’s Disease
    Christopher A. Hostage, Kingshuk Roy Choudhury, Pudugramam Murali Doraiswamy, Jeffrey R. Petrella, Alzheimer’s Disease Neuroimaging Initiative · 2013 · PLoS ONE
24. Transcriptome-guided amyloid imaging genetic analysis via a novel structured sparse learning algorithm
    Jingwen Yan, Lei Du, Sungeun Kim, Shannon L. Risacher, Heng Huang, Jason H. Moore, Andrew J. Saykin, Li Shen, Alzheimer’s Disease Neuroimaging Initiative · 2014 · Bioinformatics
25. Imaging mass spectrometry (IMS) of cortical lipids from preclinical to severe stages of Alzheimer's disease
    E. Gónzalez de San Román, Iván Manuel, Maria Teresa Giralt, Isidró Ferrer, Rafael Rodríguez‐Puertas · 2017 · Biochimica et Biophysica Acta (BBA) - Biomembranes
26. Portable magnetic resonance imaging of patients indoors, outdoors and at home
    Teresa Guallart‐Naval, José Miguel Algarín, Rubén Pellicer-Guridi, Fernando Galve, Yolanda Vives‐Gilabert, Rubén Bosch, Eduardo Pallás, José M. González, Juan Pablo Rigla, Pablo Martínez et al. · 2022 · Scientific Reports
27. Emerging β-amyloid pathology and accelerated cortical atrophy
    Mattsson, Niklas, Insel, Philip S., Nosheny, Rachel, Tosun, Duygu, Trojanowski, John Q., Shaw, Leslie M., Jack, Clifford R., Donohue, Michael C., Weiner, Michael W. · 2014 · JAMA Neurology
28. Therapeutic noninvasive brain stimulation in Alzheimer's disease and related dementias
    Stephanie S. Buss, Peter J. Fried, Álvaro Pascual‐Leone · 2019 · Current Opinion in Neurology
29. Fyn kinase inhibition reduces protein aggregation, increases synapse density and improves memory in transgenic and traumatic Tauopathy
    Si Jie Tang, Arman Fesharaki‐Zadeh, Hideyuki Takahashi, Sarah Helena Nies, Levi M. Smith, Anin Luo, Annabel S. Chyung, Marius Chiasseu, Stephen M. Strittmatter · 2020 · Acta Neuropathologica Communications
30. Multi-Task Weakly-Supervised Attention Network for Dementia Status Estimation With Structural MRI
    Chunfeng Lian, Mingxia Liu, Li Wang, Dinggang G. Shen · 2021 · IEEE Transactions on Neural Networks and Learning Systems
31. Value of Neuropsychological Tests, Neuroimaging, and Biomarkers for Diagnosing Alzheimer's Disease in Younger and Older Age Cohorts
    Ben A. Schmand, Piet Eikelenboom, Willem A. van Gool, the Alzheimer's Disease Neuroimaging Initiative · 2011 · Journal of the American Geriatrics Society
32. Comparison of qualitative and quantitative imaging characteristics of [11C]PiB and [18F]flutemetamol in normal control and Alzheimer's subjects
    James M. Mountz, Charles M. Laymon, Ann D. Cohen, Zheng Zhang, Julie C. Price, Sanaa Boudhar, Eric McDade, Howard Jay Aizenstein, William Edward Klunk, Chester A. Mathis · 2015 · NeuroImage Clinical
33. Sensitivity of voxel-based morphometry analysis to choice of imaging protocol at 3 T
    Christine Lucas Tardif, D. Louis Collins, G. Bruce Pike · 2008 · NeuroImage
34. Validating GWAS-Identified Risk Loci for Alzheimer’s Disease in Han Chinese Populations
    Hui-Zhen Wang, Rui Bi, Qiu-Xiang Hu, Qun Xiang, Chen Zhang, Dengfeng Zhang, Wen Zhang, Xiaohong Ma, Wanjun Guo, Wei Deng et al. · 2014 · Molecular Neurobiology
35. Ensemble Classification of Alzheimer's Disease and Mild Cognitive Impairment Based on Complex Graph Measures from Diffusion Tensor Images
    Ashkan Ebadi, Josué Luiz Dalboni da Rocha, Dushyanth B. Nagaraju, Fernanda Freire Tovar-Moll, Ivanei Edson Bramati, Gabriel Coutinho, Ranganatha Sitaram, Parisa Rashidi · 2017 · Frontiers in Neuroscience
36. An Optimized PatchMatch for multi-scale and multi-feature label fusion
    Rémi Giraud, Vinh‐Thong Ta, Nicolas Papadakis, José V. Manjón, D. Louis Collins, Pierrick Coupé A · 2015 · NeuroImage
37. Discrimination and conversion prediction of mild cognitive impairment using convolutional neural networks
    The Alzheimer’s Disease Neuroimaging Initiative, Congling Wu, Shengwen Guo, Yan-jia Hong, Ben‐Heng Xiao, Yu‐Peng Wu, Qin Zhang · 2018 · Quantitative Imaging in Medicine and Surgery
38. Performing different kinds of physical exercise differentially attenuates the genetic effects on obesity measures: Evidence from 18,424 Taiwan Biobank participants
    Wan‐Yu Lin, Chang‐Chuan Chan, Yu-Li Liu, Albert C. Yang, Shih‐Jen Tsai, Po‐Hsiu Kuo · 2019 · PLoS Genetics
39. Cerebellar Volume Is Associated with Cognitive Decline in Mild Cognitive Impairment: Results from ADNI
    Chi-Ying Roy Lin, Chi‐Hua Chen, Sarah E. Tom, Sheng‐Han Kuo, Alzheimer’s Disease Neuroimaging Initiative · 2020 · The Cerebellum
40. DeepCSR: A 3D Deep Learning Approach for Cortical Surface Reconstruction
    Rodrigo Santa Cruz, Léo Lebrat, Pierrick Bourgeat, Clinton Fookes, Jürgen Fripp, Olivier Salvado · 2021 · IEEE Winter Conference on Applications of Computer Vision
41. FAF-DRVFL: Fuzzy activation function based deep random vector functional links network for early diagnosis of Alzheimer disease
    Rahul Sharma, Tripti Goel, M. Tanveer, Shubham Dwivedi, R. Murugan · 2021 · Applied Soft Computing
42. Challenges for machine learning in clinical translation of big data imaging studies
    Nicola K. Dinsdale, Emma Bluemke, Vaanathi Sundaresan, Mark Jenkinson, Stephen M. Smith, Ana I. L. Namburete · 2022 · Neuron
43. Florbetapir PET, FDG PET, and MRI in Down syndrome individuals with and without Alzheimer's dementia
    Marwan Noel Sabbagh, Kewei Chen, Joseph Rogers, Adam Fleisher, Carolyn Liebsack, Dan Bandy, Christine M. Belden, Hillary D. Protas, Pradeep Thiyyagura, Xiaofen Liu et al. · 2015 · Alzheimer s & Dementia
44. Right Anterior Insula: Core Region of Hallucinations in Cognitive Neurodegenerative Diseases
    Frédéric Blanc, Vincent Noblet, Nathalie Philippi, Benjamin Cretin, Jack Foucher, Jean‐Paul Armspach, François Rousseau, the Alzheimer's Disease Neuroimaging Initiative · 2014 · PLoS ONE
45. Consistent multi-time-point brain atrophy estimation from the boundary shift integral
    Kelvin K. Leung, Gerard R. Ridgway, Sebastien Ourselin A, Nick C. Fox · 2011 · NeuroImage
46. Deep learning of texture and structural features for multiclass Alzheimer's disease classification
    Chester V. Dolph, Mahbubul Alam, Zeina A. Shboul, Manar D. Samad, Khan M. Iftekharuddin · 2017 · International Joint Conference on Neural Networks (IJCNN)
47. Sex differences in the association between apolipoprotein E ε4 allele and Alzheimer's disease markers
    Erin E. Sundermann, My Tran, Pauline M. Maki, Mark William Bondi, Alzheimer’s Disease Neuroimaging Initiative · 2018 · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring
48. MR‐based age‐related effects on the striatum, globus pallidus, and thalamus in healthy individuals across the adult lifespan
    Stéphanie Tullo, Raihaan Patel, Gabriel A. Devenyi, Alyssa Salaciak, Saashi A. Bedford, Sarah Farzin, Nancy Wlodarski, Christine Lucas Tardif, John C.S. Breitner, M. Mallar Chakravarty · 2019 · Human Brain Mapping
49. Applying Automated MR-Based Diagnostic Methods to the Memory Clinic: A Prospective Study
    Klöppel, Stefan, Peter, Jessica, Ludl, Anna, Pilatus, Anne, Maier, Sabrina, Mader, Irina, Heimbach, Bernhard, Frings, Lars, Egger, Karl, Dukart, Juergen et al. · 2015 · Journal of Alzheimer’s Disease
50. Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease
    Biao Jie, Mingxia Liu, Jun Liu, Daoqiang Zhang, Dinggang G. Shen · 2016 · IEEE Transactions on Biomedical Engineering
51. Data analysis with Shapley values for automatic subject selection in Alzheimer’s disease data sets using interpretable machine learning
    Bloch, Louise, Friedrich, Christoph M., for the Alzheimer’s Disease Neuroimaging Initiative · 2021 · Alzheimer's Research & Therapy
52. Combining 3D Image and Tabular Data via the Dynamic Affine Feature Map Transform
    Sebastian Pölsterl, Tom Nuno Wolf, Christian Wachinger · 2021 · Lecture notes in computer science
53. Efficient self-attention mechanism and structural distilling model for Alzheimer’s disease diagnosis
    Jiayi Zhu, Ying Hui Valerie Tan, Rude Lin, Jiaqing Miao, Xuwei Fan, Yafei Zhu, Ping Liang, Jinnan Gong, Hui He · 2022 · Computers in Biology and Medicine
54. A systematic review of generalization research in medical image classification
    Sarah Christina Matta, Mathieu Lamard, Philippe Zhang, Alexandre Le Guilcher, Laurent Borderie, Béatrice Cochener, Gwenolé Quellec · 2024 · Computers in Biology and Medicine
55. Increased putamen and callosal motor subregion in treatment‐naïve boys with Tourette syndrome indicates changes in the bihemispheric motor network
    Veit Roessner, Sebastian Overlack, Carsten Schmidt‐Samoa, Jürgen Baudewig, Peter Dechent, Aribert Rothenberger, Gunther Helms · 2010 · Journal of Child Psychology and Psychiatry
56. Fluid and white matter suppression with the MP2RAGE sequence
    Mark Tanner, Giulio Gambarota, Tobias Kober, Gunnar Krüger, David Erritzøe, José P. Marques, Rexford D. Newbould · 2011 · Journal of Magnetic Resonance Imaging
57. Detecting brain structural changes as biomarker from magnetic resonance images using a local feature based SVM approach
    Ye Chen, Judd M. Storrs, Lirong Tan, Lawrence J. Mazlack, J. H. Lee, Long Jason Lu · 2013 · Journal of Neuroscience Methods
58. Accurate Prediction of Conversion to Alzheimer’s Disease using Imaging, Genetic, and Neuropsychological Biomarkers
    Juergen Dukart, Fabio Sambataro, Alessandro Bertolino, Alzheimer’s Disease Neuroimaging Initiative · 2015 · Journal of Alzheimer s Disease
59. An ensemble learning system for a 4-way classification of Alzheimer’s disease and mild cognitive impairment
    Dongren Yao, Vince D. Calhoun, Zening Fu, Yuhui Du, Jing Sui （Beijing Normal University）， my correct affiliation is beijing normal university, not Qingdao University of Science and Technology, please correct the current affiliation. Thank you · 2018 · Journal of Neuroscience Methods
60. The relevance of cerebrospinal fluid α-synuclein levels to sporadic and familial Alzheimer’s disease
    for the Dominantly Inherited Alzheimer Network (DIAN), Twohig, Daniel, Rodriguez-Vieitez, Elena, Sando, Sigrid B., Berge, Guro, Lauridsen, Camilla, Møller, Ina, Grøntvedt, Gøril R., Bråthen, Geir, Patra, Kalicharan et al. · 2018 · Acta Neuropathologica Communications
61. Brain-Derived Neurotrophic Factor Serum Levels and Hippocampal Volume in Mild Cognitive Impairment and Dementia due to Alzheimer Disease
    Borba, Ericksen Mielle, Duarte, Juliana Avila, Bristot, Giovana, Scotton, Ellen, Camozzato, Ana Luiza, Chaves, Márcia Lorena Fagundes · 2016 · Dementia and Geriatric Cognitive Disorders Extra
62. Systematic review of strengths and limitations of Randomized Controlled Trials for non-pharmacological interventions in mild cognitive impairment: Focus on Alzheimer's disease
    Horr, T., Messinger-Rapport, B., Pillai, Jagan A. · 2015 · The Journal of nutrition, health and aging
63. Biomarkers in translational research of Alzheimer’s Disease
    Tarawneh, Rawan, Holtzman, David M. · 2010 · Neuropharmacology
64. Multiple Landmark Detection Using Multi-agent Reinforcement Learning
    Athanasios Vlontzos, Amir Alansary, Konstantinos Kamnitsas, Daniel Rueckert, Bernhard Kainz · 2019 · Lecture notes in computer science
65. Deep Convolutional Neural Network based Classification of Alzheimer's Disease using MRI Data
    Ali Nawaz, Syed Muhammad Anwar, Rehan Liaqat, Javid Iqbal, Ulaş Bağcı, Muhammad Majid · 2020 · IEEE International Multitopic Conference (INMIC)
66. Applied machine learning in Alzheimer's disease research: omics, imaging, and clinical data
    Ziyi Li, Xiaoqian Jiang, Yizhuo Wang, Yejin Kim · 2021 · Emerging Topics in Life Sciences
67. OpenBHB: a Large-Scale Multi-Site Brain MRI Data-set for Age Prediction and Debiasing
    Benoît Dufumier, Antoine Grigis, Julie Victor, Corentin Ambroise, Vincent Frouin, Édouard Duchesnay · 2022 · NeuroImage
68. Unsupervised cross-domain functional MRI adaptation for automated major depressive disorder identification
    Yuqi Fang, Mingliang Wang, Guy G. Potter, Mingxia Liu · 2022 · Medical Image Analysis
69. Joint transformer architecture in brain 3D MRI classification: its application in Alzheimer’s disease classification
    Sait Alp, Taymaz Akan, Md. Shenuarin Bhuiyan, Elizabeth A. Disbrow, Steven A. Conrad, John A. Vanchiere, Christopher G. Kevil, Mohammad Alfrad Nobel Bhuiyan · 2024 · Scientific Reports
70. Homocysteine effects on brain volumes mapped in 732 elderly individuals
    Priya Rajagopalan, Xue Hua, Arthur W. Toga, Clifford R. Jack, Michael Walter Weiner, Paul M. Thompson · 2011 · Neuroreport
71. Machine-learning techniques for building a diagnostic model for very mild dementia
    Rong Chen, Edward H. Herskovits · 2010 · NeuroImage
72. Classification and prediction of clinical diagnosis of Alzheimer's disease based on MRI and plasma measures of α‐/γ‐tocotrienols and γ‐tocopherol
    Francesca Mangialasche, Eric Westman, Miia Kivipelto, J‐Sebastian Muehlboeck, Roberta Cecchetti, Mauro Baglioni, R. Tarducci, Gianni Gobbi, Piero Floridi, Hilkka S. Soininen et al. · 2013 · Journal of Internal Medicine
73. Impaired Parahippocampus Connectivity in Mild Cognitive Impairment and Alzheimer’s Disease
    Jieqiong Liu, Xinqing Zhang, Chunshui Yu, Yunyun Duan, Junjie Zhuo, Yue Julia Cui, Bing Liu, Kuncheng Li, Tianzi Jiang, Yong Liu · 2015 · Journal of Alzheimer s Disease
74. Classification of Alzheimer's Disease Structural MRI Data by Deep Learning Convolutional Neural Networks
    Saman Sarraf, Ghassem Tofighi · 2016 · arXiv (Cornell University)
75. Generation and quality control of lipidomics data for the alzheimer’s disease neuroimaging initiative cohort
    Barupal, Dinesh Kumar, Fan, Sili, Wancewicz, Benjamin, Cajka, Tomas, Sa, Michael, Showalter, Megan R., Baillie, Rebecca, Tenenbaum, Jessica D., Louie, Gregory, Alzheimer’s Disease Neuroimaging Initiative et al. · 2018 · Scientific Data
76. Identifying canonical and replicable multi‐scale intrinsic connectivity networks in 100k+ resting‐state fMRI datasets
    Armin Iraji, Zening Fu, Ashkan Faghiri, Marlena Duda, J. Chen, Srinivas Rachakonda, Thomas P. DeRamus, Peter V Kochunov, Bhim Mani Adhikari, Ayşenil Belger et al. · 2023 · Human Brain Mapping
77. Head motion detection using FID navigators
    Tobias Kober, José P. Marques, Rolf Gruetter A, Gunnar Krüger · 2011 · Magnetic Resonance in Medicine
78. Inter-site Variability in Prostate Segmentation Accuracy Using Deep Learning
    Eli Gibson, Yipeng Hu, Nooshin Ghavami, Hashim Uddin Ahmed, Caroline M. Moore, Mark Emberton, HenkJan J. Huisman, Dean C. Barratt · 2018 · Lecture notes in computer science
79. CSF Apo-E levels associate with cognitive decline and MRI changes
    For the Alzheimer’s Disease Neuroimaging Initiative, Toledo, Jon B., Da, Xiao, Weiner, Michael W., Wolk, David A., Xie, Sharon X., Arnold, Steven E., Davatzikos, Christos, Shaw, Leslie M., Trojanowski, John Q. · 2014 · Acta Neuropathologica
80. Machine Learning for Neurodegenerative Disorder Diagnosis — Survey of Practices and Launch of Benchmark Dataset
    Athanasios Tagaris, Dimitrios Kollias, Andreas Stafylopatis, Georgios L. Tagaris, Stefanos Kollias · 2018 · International Journal of Artificial Intelligence Tools
81. The Association Between Biomarkers and Neuropsychiatric Symptoms Across the Alzheimer's Disease Spectrum
    Leonie C. P. Banning, Inez H.G.B. Ramakers, Sebastian Köhler, Esther E. Bron, Frans R.J. Verhey, Peter Paul De Deyn, Jurgen A.H.R. Claassen, Huiberdina L. Koek, Huub A. M. Middelkoop, Wiesje M. van der Flier et al. · 2020 · American Journal of Geriatric Psychiatry
82. The cholinergic system in subtypes of Alzheimer’s disease: an in vivo longitudinal MRI study
    Alejandra Machado, Daniel Ferreira, Michel J. Grothe, Helga Eyjolfsdottir, Per M. Almqvist, Lena Cavallin, Göran Lind, Göran Lind, Åke Seiger, Stefan Teipel et al. · 2020 · Alzheimer s Research & Therapy
83. Regional Radiomics Similarity Networks Reveal Distinct Subtypes and Abnormality Patterns in Mild Cognitive Impairment
    Kun Zhao, Qiang Zheng, Martin Dyrba, Timothy Rittman, Ang Li, Tongtong Che, Pindong Chen, Yuqing Sun, Xiaopeng Kang, Qiongling Li et al. · 2022 · Advanced Science
84. CNN and swin-transformer based efficient model for Alzheimer’s disease diagnosis with sMRI
    Jiaming Xin, Ancong Wang, Rui Juan Guo, Weifeng Liu, Xiaoying Tang · 2023 · Biomedical Signal Processing and Control
85. Comprehensive review of Transformer‐based models in neuroscience, neurology, and psychiatry
    Shan Cong, Hang Wang, Yang Zhou, Zheng Wang, Xiaohui Yao, Chunsheng Yang · 2024 · Brain‐X
86. Lifetime History of Depression Predicts Increased Amyloid-β Accumulation in Patients with Mild Cognitive Impairment
    Jun Ku Chung, Alzheimer’s Disease Neuroimaging Initiative, Eric Plitman, Shinichiro Nakajima, Tiffany W. Chow, M. Mallar Chakravarty, Fernando Caravaggio, Philip Gerretsen, Eric E. Brown, Yusuke Iwata et al. · 2015 · Journal of Alzheimer s Disease
87. The Worldwide Alzheimer's Disease Neuroimaging Initiative: An update
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88. Higher homocysteine associated with thinner cortical gray matter in 803 participants from the Alzheimer's Disease Neuroimaging Initiative
    Sarah K. Madsen, Priya Rajagopalan, Shantanu H. Joshi, Arthur W. Toga, Paul M. Thompson · 2014 · Neurobiology of Aging
89. Multiple loci influencing hippocampal degeneration identified by genome scan
    Scott A. Melville, Jacqueline L. Buros, Antonio Parrado, Badri Narayan Vardarajan, Mark W. Logue, Li Shen, Shannon L. Risacher, Sungeun Kim, Gyungah Jun, Charles S DeCarli et al. · 2012 · Annals of Neurology
90. Advances in MRI Biomarkers for the Diagnosis of Alzheimer’s Disease
    Elizabeth G. Kehoe, Jonathan P McNulty, Paul Gerald Mullins, Arun L.W. Bokde · 2014 · Biomarkers in Medicine
91. Impaired topological architecture of brain structural networks in idiopathic Parkinson’s disease: a DTI study
    Changhong Li, Biao Huang, Ruibin Zhang, Qing Ma, Wanqun Yang, Lijuan Wang, Limin Wang, Qin Xu, Jieying Feng, Liqing Liu et al. · 2016 · Brain Imaging and Behavior
92. The cerebellum shrinks faster than normal ageing in A lzheimer's disease but not in mild cognitive impairment
    Hossein Tabatabaei‐Jafari, Erin Walsh, Marnie Evelyn Shaw, Nicolas Cherbuin, Alzheimer’s Disease Neuroimaging Initiative · 2017 · Human Brain Mapping
93. Combined Effects of Alzheimer Risk Variants in the <i>CLU</i> and <i>ApoE</i> Genes on Ventricular Expansion Patterns in the Elderly
    Roussotte, Florence F., Gutman, Boris A., Madsen, Sarah K., Colby, John B., Thompson, Paul M., for the Alzheimer's Disease Neuroimaging Initiative · 2014 · The Journal of Neuroscience
94. Toward an interpretable Alzheimer’s disease diagnostic model with regional abnormality representation via deep learning
    Lee, Eunho, Choi, Jun-Sik, Kim, Minjeong, Suk, Heung-Il · 2019 · NeuroImage
95. Regional heterogeneity in limbic maturational changes: Evidence from integrating cortical thickness, volumetric and diffusion tensor imaging measures
    Grieve, Stuart M., Korgaonkar, Mayuresh S., Clark, C. Richard, Williams, Leanne M. · 2011 · NeuroImage
96. Identifying the Neuroanatomical Basis of Cognitive Impairment in Alzheimer's Disease by Correlation- and Nonlinearity-Aware Sparse Bayesian Learning
    Jing Wan, Zhilin Zhang, Bhaskar D. Rao, Shiaofen Fang, Jingwen Yan, Andrew J. Saykin, Li Shen · 2014 · IEEE Transactions on Medical Imaging
97. Model Based on Deep Feature Extraction for Diagnosis of Alzheimer’s Disease
    Iago R. R. Silva, Gabriela dos Santos Lucas e Silva, Rodrigo Gomes de Souza, Wellington Pinheiro dos Santos, Roberta Fagundes · 2019 · International Joint Conference on Neural Networks (IJCNN)
98. Direct cortical thickness estimation using deep learning‐based anatomy segmentation and cortex parcellation
    Michael Rebsamen, Christian Rummel, Mauricio Reyes, Roland Wiest, Richard McKinley · 2020 · Human Brain Mapping
99. Longitudinal plasma phosphorylated tau 181 tracks disease progression in Alzheimer’s disease
    Shi-Dong Chen, Yuyuan Huang, Xue‐Ning Shen, Yu Guo, Lan Tan, Qiang Dong, Jin‐Tai Yu, Alzheimer’s Disease Neuroimaging Initiative · 2021 · Translational Psychiatry
100. Deep neural network heatmaps capture Alzheimer’s disease patterns reported in a large meta-analysis of neuroimaging studies
     Di Wang, Nicolas Honnorat, Peter T. Fox, Kerstin Ritter, Simon Bodo Eickhoff, Sudha S. Seshadri, Mohamad Habes · 2023 · NeuroImage