Alzheimer's Disease Neuroimaging Initiative

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Viewing Publication 1 - 89 from 89

2024

BASE: Brain Age Standardized EvaluationLara Dular, Ziga Spiclin, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 285:120469, January 2024. [doi]

Data-driven stochastic model for quantifying the interplay between amyloid-beta and calcium levels in Alzheimer's diseaseHina Shaheen, Roderick Melnik, Sundeep Singh, Alzheimer's Disease Neuroimaging Initiative. sadm, 17(2), April 2024. [doi]

2023

Orthogonal latent space learning with feature weighting and graph learning for multimodal Alzheimer's disease diagnosisZhi Chen, Yongguo Liu, Yun Zhang, Qiaoqin Li, Alzheimer's Disease Neuroimaging Initiative. mia, 84:102698, 2023. [doi]

Auditing Unfair Biases in CNN-Based Diagnosis of Alzheimer's DiseaseVien Ngoc Dang, Adrià Casamitjana, Martijn P. A. Starmans, Carlos Martín-Isla, Jerónimo Hernández-González, Karim Lekadir, Alzheimer's Disease Neuroimaging Initiative. clip-ws 2023: 172-182 [doi]

Alzheimer's disease classification based on graph kernel SVMs constructed with 3D texture features extracted from MR imagesLucas José Cruz de Mendonça, Ricardo José Ferrari, Alzheimer's Disease Neuroimaging Initiative. eswa, 211:118633, 2023. [doi]

Predicting the evolution trajectory of population-driven connectional brain templates using recurrent multigraph neural networksOytun Demirbilek, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative. mia, 83:102649, 2023. [doi]

A Multi-Modality Approach to Medical Case Retrieval for Alzheimer's DiseaseKatarina Trojachanec Dineva, Ivan Kitanovski, Ivica Dimitrovski, Suzana Loshkovska, Alzheimer's Disease Neuroimaging Initiative. biostec 2023: 554-561 [doi]

SUVR quantification using attention-based 3D CNN with longitudinal Florbetapir PET images in Alzheimer's diseaseR. Divya, R. Shantha Selva Kumari, Alzheimer's Disease Neuroimaging Initiative. bspc, 86(Part B):105254, September 2023. [doi]

Template-based graph registration network for boosting the diagnosis of brain connectivity disordersZeynep Gürler, Mohammed Amine Gharsallaoui, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative. cmig, 103:102140, 2023. [doi]

Identifying Modality-Consistent and Modality-Specific Features via Label-Guided Multi-Task Sparse Canonical Correlation Analysis for Neuroimaging GeneticsXiaoke Hao, Qihao Tan, Yingchun Guo, Yunjia Xiao, Ming Yu 0006, Meiling Wang, Jing Qin 0001, Daoqiang Zhang, Alzheimer's Disease Neuroimaging Initiative. tbe, 70(3):831-840, March 2023. [doi]

Universum twin support vector machine with truncated pinball lossAnuradha Kumari, M. Tanveer 0001, Alzheimer's Disease Neuroimaging Initiative. eaai, 123(Part C):106427, 2023. [doi]

Graph neural network based unsupervised influential sample selection for brain multigraph population fusionMert Can Kurucu, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative. cmig, 108:102274, September 2023. [doi]

A Convolutional Neural Network and Graph Convolutional Network Based Framework for AD ClassificationLan Lin, Min Xiong, Ge Zhang, Wenjie Kang, Shen Sun, Shuicai Wu, Alzheimer's Disease Neuroimaging Initiative. sensors, 23(4):1914, February 2023. [doi]

Monte Carlo Ensemble Neural Network for the diagnosis of Alzheimer's diseaseChaoqiang Liu, Fei Huang, Anqi Qiu, Alzheimer's Disease Neuroimaging Initiative. NN, 159:14-24, February 2023. [doi]

MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer's disease progression modellingGerard Martí-Juan, Marco Lorenzi, Gemma Piella, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 268:119892, March 2023. [doi]

Classification of cognitively normal controls, mild cognitive impairment and Alzheimer's disease using transfer learning approachV. P. Subramanyam Rallabandi, K. Seetharaman, Alzheimer's Disease Neuroimaging Initiative. bspc, 79(Part):104092, 2023. [doi]

Enhanced brain efficiency network by integrating the new causality with fMRI and its application for Alzheimer's Disease studyBocheng Wang, Alzheimer's Disease Neuroimaging Initiative. bspc, 86(Part C):105364, September 2023. [doi]

The Objective Dementia Severity Scale Based on MRI with Contrastive Learning: A Whole Brain Neuroimaging PerspectiveYike Zhang, Wenliang Fan, Xi Chen, Wei Li 0086, Alzheimer's Disease Neuroimaging Initiative. sensors, 23(15):6871, August 2023. [doi]

2022

Classifying Alzheimer's Disease using MRIs and Transcriptomic DataLucia Maddalena 0001, Ilaria Granata, Maurizio Giordano, Mario Manzo, Mario Rosario Guarracino, Alzheimer's Disease Neuroimaging Initiative. biostec 2022: 70-79 [doi]

Characterizing the propagation pathway of neuropathological events of Alzheimer's disease using harmonic wavelet analysisJiazhou Chen, Hongmin Cai, Defu Yang, Martin Styner, Guorong Wu 0001, Alzheimer's Disease Neuroimaging Initiative. mia, 79:102446, 2022. [doi]

Detection of Alzheimer's disease using features of brain region-of-interest-based individual network constructed with the sMRI imageJinwang Feng, Shaowu Zhang 0001, Luonan Chen, Chunman Zuo, Alzheimer's Disease Neuroimaging Initiative. cmig, 98:102057, 2022. [doi]

KNN weighted reduced universum twin SVM for class imbalance learningM. A. Ganaie, Mohammad Tanveer 0001, Alzheimer's Disease Neuroimaging Initiative. kbs, 245:108578, 2022. [doi]

Quantifying the reproducibility of graph neural networks using multigraph data representationAhmed Nebli, Mohammed Amine Gharsallaoui, Zeynep Gürler, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative. NN, 148:254-265, 2022. [doi]

Development and evaluation of a high resolution 0.5mm isotropic T1-weighted template of the older adult brainMohammad Rakeen Niaz, Abdur Raquib Ridwan, Yingjuan Wu, Alzheimer's Disease Neuroimaging Initiative, David A. Bennett, Konstantinos Arfanakis. neuroimage, 248:118869, 2022. [doi]

A deep ensemble hippocampal CNN model for brain age estimation applied to Alzheimer's diagnosisKatia Maria Poloni, Ricardo José Ferrari, Alzheimer's Disease Neuroimaging Initiative. eswa, 195:116622, 2022. [doi]

DAFT: A universal module to interweave tabular data and 3D images in CNNsTom Nuno Wolf, Sebastian Pölsterl, Christian Wachinger, Alzheimer's Disease Neuroimaging Initiative, Australian Imaging Biomarkers Lifestyle flagship study of ageing. neuroimage, 260:119505, 2022. [doi]

1-weighted and diffusion tensor templates of the older adult brain in a common spaceYingjuan Wu, Abdur Raquib Ridwan, Mohammad Rakeen Niaz, Xiaoxiao Qi, Shengwei Zhang, Alzheimer's Disease Neuroimaging Initiative, David A. Bennett, Konstantinos Arfanakis. neuroimage, 260:119417, 2022. [doi]

Predicting brain structural network using functional connectivityLu Zhang, Li Wang, Dajiang Zhu, Alzheimer's Disease Neuroimaging Initiative. mia, 79:102463, 2022. [doi]

2021

3D shearlet-based descriptors combined with deep features for the classification of Alzheimer's disease based on MRI dataSadiq Alinsaif, Jochen Lang 0001, Alzheimer's Disease Neuroimaging Initiative. cbm, 138:104879, 2021. [doi]

Bloch modelling enables robust T2 mapping using retrospective proton density and T2-weighted images from different vendors and sitesGitanjali Chhetri, Kelly C. McPhee, Alan H. Wilman, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 237:118116, 2021. [doi]

Identifying associations among genomic, proteomic and imaging biomarkers via adaptive sparse multi-view canonical correlation analysisLei Du, Jin Zhang, Fang Liu, Huiai Wang, Lei Guo, Junwei Han, Alzheimer's Disease Neuroimaging Initiative. mia, 70:102003, 2021. [doi]

Fuzzy least squares projection twin support vector machines for class imbalance learningM. A. Ganaie, Muhammad Tanveer 0001, Alzheimer's Disease Neuroimaging Initiative. asc, 113(Part):107933, 2021. [doi]

Investigating hypotheses of neurodegeneration by learning dynamical systems of protein propagation in the brainSara Garbarino, Marco Lorenzi, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 235:117980, 2021. [doi]

Obtaining leaner deep neural networks for decoding brain functional connectome in a single shotSukrit Gupta, Yi Hao Chan, Jagath C. Rajapakse, Alzheimer's Disease Neuroimaging Initiative. ijon, 453:326-336, 2021. [doi]

Fast mesh data augmentation via Chebyshev polynomial of spectral filteringShih-Gu Huang, Moo K. Chung, Anqi Qiu, Alzheimer's Disease Neuroimaging Initiative. NN, 143:198-208, 2021. [doi]

Deep recurrent model for individualized prediction of Alzheimer's disease progressionWonsik Jung, Eunji Jun, Heung-Il Suk, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 237:118143, 2021. [doi]

Translating amyloid PET of different radiotracers by a deep generative model for interchangeabilitySeung Kwan Kang, Hongyoon Choi, Jae Sung Lee, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 232:117890, 2021. [doi]

A novel method for the classification of Alzheimer's disease from normal controls using magnetic resonance imagingRiyaj Uddin Khan, Mohammad Tanveer 0001, Ram Bilas Pachori, Alzheimer's Disease Neuroimaging Initiative. es, 38(1), 2021. [doi]

A unified framework for personalized regions selection and functional relation modeling for early MCI identificationJiyeon Lee, Wonjun Ko, Eunsong Kang, Heung-Il Suk, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 236:118048, 2021. [doi]

A predictive framework based on brain volume trajectories enabling early detection of Alzheimer's diseaseSamaneh Abolpour Mofrad, Arvid Lundervold, Alexander Selvikvåg Lundervold, Alzheimer's Disease Neuroimaging Initiative. cmig, 90:101910, 2021. [doi]

Using ProtoPNet for Interpretable Alzheimer's Disease ClassificationSanaz Mohammadjafari, Mucahit Cevik, Mathusan Thanabalasingam, Ayse Basar, Alzheimer's Disease Neuroimaging Initiative. ai 2021: [doi]

Combined Atlas and Convolutional Neural Network-Based Segmentation of the Hippocampus from MRI According to the ADNI Harmonized ProtocolSamaneh Nobakht, Morgan Schaeffer, Nils D. Forkert, Sean M. Nestor, Sandra E. Black, Philip Barber, Alzheimer's Disease Neuroimaging Initiative. sensors, 21(7):2427, 2021. [doi]

Permutation-based inference for spatially localized signals in longitudinal MRI dataJun-Young Park, Mark Fiecas, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 239:118312, 2021. [doi]

Brain MR image classification for Alzheimer's disease diagnosis using structural hippocampal asymmetrical attributes from directional 3-D log-Gabor filter responsesKatia Maria Poloni, Italo Antonio Duarte de Oliveira, Roger Tam, Ricardo José Ferrari, Alzheimer's Disease Neuroimaging Initiative. ijon, 419:126-135, 2021. [doi]

Network propagation of rare variants in Alzheimer's disease reveals tissue-specific hub genes and communitiesMarzia Antonella Scelsi, Valerio Napolioni, Michael D. Greicius, André Altmann, Alzheimer's Disease Neuroimaging Initiative, Alzheimer's Disease Sequencing Project. ploscb, 17(1), 2021. [doi]

Testing conditional mean through regression model sequence using Yanai's generalized coefficient of determinationMasao Ueki, Alzheimer's Disease Neuroimaging Initiative. csda, 158:107168, 2021. [doi]

Learning to synthesise the ageing brain without longitudinal dataTian Xia, Agisilaos Chartsias, Chengjia Wang, Sotirios A. Tsaftaris, Alzheimer's Disease Neuroimaging Initiative. mia, 73:102169, 2021. [doi]

2020

Cortical surface registration using unsupervised learningJieyu Cheng, Adrian V. Dalca, Bruce Fischl, Lilla Zöllei, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 221:117161, 2020. [doi]

Estimation of connectional brain templates using selective multi-view network normalizationSalma Dhifallah, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative. mia, 59, 2020. [doi]

Identifying the best data-driven feature selection method for boosting reproducibility in classification tasksNicolas Georges, Islem Mhiri, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative. PR, 101:107183, 2020. [doi]

Bayesian GWAS with Structured and Non-Local PriorsAdam Kaplan, Eric F. Lock, Mark Fiecas, Alzheimer's Disease Neuroimaging Initiative. bioinformatics, 36(1):17-25, 2020. [doi]

Monotonic Gaussian Process for spatio-temporal disease progression modeling in brain imaging dataClement Abi Nader, Nicholas Ayache, Philippe Robert, Marco Lorenzi, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 205, 2020. [doi]

Quantifying uncertainty in brain-predicted age using scalar-on-image quantile regressionMarco Palma, Shahin Tavakoli, Julia Brettschneider, Thomas E. Nichols, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 219:116938, 2020. [doi]

Targeting the uncertainty of predictions at patient-level using an ensemble of classifiers coupled with calibration methods, Venn-ABERS, and Conformal Predictors: A case study in ADTelma Pereira, Sandra Cardoso, Manuela Guerreiro, Alexandre de Mendonça, Sara C. Madeira, Alzheimer's Disease Neuroimaging Initiative. jbi, 101:103350, 2020. [doi]

Least squares projection twin support vector clustering (LSPTSVC)Bharat Richhariya, Muhammad Tanveer 0001, Alzheimer's Disease Neuroimaging Initiative. isci, 533:1-23, 2020. [doi]

Diagnosis of Alzheimer's disease using universum support vector machine based recursive feature elimination (USVM-RFE)Bharat Richhariya, Muhammad Tanveer 0001, A. H. Rashid, Alzheimer's Disease Neuroimaging Initiative. bspc, 59:101903, 2020. [doi]

Protein-protein interactions in neurodegenerative diseases: A conspiracy theoryTravis B. Thompson, Pavanjit Chaggar, Ellen Kuhl, Alain Goriely, Alzheimer's Disease Neuroimaging Initiative. ploscb, 16(10), 2020. [doi]

Building machine learning models without sharing patient data: A simulation-based analysis of distributed learning by ensemblingAnup Tuladhar, Sascha Gill, Zahinoor Ismail, Nils D. Forkert, Alzheimer's Disease Neuroimaging Initiative. jbi, 106:103424, 2020. [doi]

Functional linear regression model with randomly censored data: Predicting conversion time to Alzheimer 's diseaseSeong J. Yang, Hyejin Shin, Sang-Han Lee, Seokho Lee, Alzheimer's Disease Neuroimaging Initiative. csda, 150:107009, 2020. [doi]

2019

RNN-based longitudinal analysis for diagnosis of Alzheimer's diseaseRuoxuan Cui, Manhua Liu, Alzheimer's Disease Neuroimaging Initiative. cmig, 73:1-10, 2019. [doi]

Identifying Glucose Metabolism Decreased Brain Regions by Independent Component Analysis and Statistical Parametric Mapping to Understand the Aging ProcessingZhan Gao, Juan Huang, Xiaxia Chen, Feifei Dong, Hui Li, Ling Shang, Xun Jiang, Ling Wei, Alzheimer's Disease Neuroimaging Initiative. jmihi, 9(9):1938-1942, 2019. [doi]

Prediction and Classification of Alzheimer's Disease Based on Combined Features From Apolipoprotein-E Genotype, Cerebrospinal Fluid, MR, and FDG-PET Imaging BiomarkersYubraj Gupta, Ramesh Kumar Lama, Goo-Rak Kwon, Alzheimer's Disease Neuroimaging Initiative. ficn, 2019:72, 2019. [doi]

Incorporating spatial-anatomical similarity into the VGWAS framework for AD biomarker detectionMeiyan Huang, Yuwei Yu, Wei Yang 0006, Qianjin Feng, Alzheimer's Disease Neuroimaging Initiative. bioinformatics, 35(24):5271-5280, 2019. [doi]

Toward an interpretable Alzheimer's disease diagnostic model with regional abnormality representation via deep learningEunho Lee, Jun-Sik Choi, Minjeong Kim, Heung-Il Suk, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 202, 2019. [doi]

Communicability disruption in Alzheimer's disease connectivity networksEufemia Lella, Nicola Amoroso, Angela Lombardi, Tommaso Maggipinto, Sabina Tangaro, Roberto Bellotti, Alzheimer's Disease Neuroimaging Initiative. compnet, 7(1):83-100, 2019. [doi]

Benchmarking machine learning models for late-onset alzheimer's disease prediction from genomic dataJavier De Velasco Oriol, Edgar E. Vallejo-Clemente, Karol Estrada, José Gerardo Taméz Peña, Alzheimer's Disease Neuroimaging Initiative. bmcbi, 20(1):709, 2019. [doi]

QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomyAbhijit Guha Roy, Sailesh Conjeti, Nassir Navab, Christian Wachinger, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 186:713-727, 2019. [doi]

Multi-modal latent factor exploration of atrophy, cognitive and tau heterogeneity in Alzheimer's diseaseNanbo Sun, Elizabeth C. Mormino, Jianzhong Chen, Mert R. Sabuncu, B. T. Thomas Yeo, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 201, 2019. [doi]

2018

Modeling and prediction of clinical symptom trajectories in Alzheimer's disease using longitudinal dataNikhil Bhagwat, Joseph D. Viviano, Aristotle N. Voineskos, M. Mallar Chakravarty, Alzheimer's Disease Neuroimaging Initiative. ploscb, 14(9), 2018. [doi]

A comparison of publicly available linear MRI stereotaxic registration techniquesMahsa Dadar, Vladimir S. Fonov, D. Louis Collins, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 174:191-200, 2018. [doi]

Joint Prediction and Classification of Brain Image Evolution Trajectories from Baseline Brain Image with Application to Early DementiaCan Gafuroglu, Islem Rekik, Alzheimer's Disease Neuroimaging Initiative. miccai 2018: 437-445 [doi]

Gaussian process uncertainty in age estimation as a measure of brain abnormalityBenjamín Gutiérrez-Becker, Tassilo Klein, Christian Wachinger, Alzheimer's Disease Neuroimaging Initiative, Australian Imaging Biomarkers & Lifestyle flagship study of ageing. neuroimage, 175:246-258, 2018. [doi]

A longitudinal model for functional connectivity networks using resting-state fMRIBrian Hart, Ivor Cribben, Mark Fiecas, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 178:687-701, 2018. [doi]

Adaptive fusion of texture-based grading for Alzheimer's disease classificationKilian Hett, Vinh-Thong Ta, José V. Manjón, Pierrick Coupé, Alzheimer's Disease Neuroimaging Initiative. cmig, 70:8-16, 2018. [doi]

Predicting conversion from MCI to AD by integrating rs-fMRI and structural MRISeyed Hani Hojjati, Ata Ebrahimzadeh, Ali Khazaee, Abbas Babajani-Feremi, Alzheimer's Disease Neuroimaging Initiative. cbm, 102:30-39, 2018. [doi]

Multimodal imaging-based therapeutic fingerprints for optimizing personalized interventions: Application to neurodegenerationYasser Iturria-Medina, Felix Carbonell, Alan C. Evans, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 179:40-50, 2018. [doi]

Classification of Alzheimer's Disease, Mild Cognitive Impairment, and Cognitively Unimpaired Individuals Using Multi-feature Kernel Discriminant Dictionary LearningQing Li, Xia Wu, Lele Xu, Kewei Chen, Li Yao, Alzheimer's Disease Neuroimaging Initiative. ficn, 2018:117, 2018. [doi]

Alzheimer's disease diagnosis based on multiple cluster dense convolutional networksFan Li, Manhua Liu, Alzheimer's Disease Neuroimaging Initiative. cmig, 70:101-110, 2018. [doi]

Neural Dynamics during Resting State: A Functional Magnetic Resonance Imaging Exploration with Reduction and VisualizationWei Li, Miao Wang, Wen Wen, Yue Huang, Xi Chen 0002, Wenliang Fan, Alzheimer's Disease Neuroimaging Initiative. complexity, 2018, 2018. [doi]

SMAC: Spatial multi-category angle-based classifier for high-dimensional neuroimaging dataLeo Yu-Feng Liu, Yufeng Liu, Hongtu Zhu, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 175:230-245, 2018. [doi]

Classification of Alzheimer's Disease by Combination of Convolutional and Recurrent Neural Networks Using FDG-PET ImagesManhua Liu, Danni Cheng, Weiwu Yan, Alzheimer's Disease Neuroimaging Initiative. fini, 2018:35, 2018. [doi]

Classification of Alzheimer's and MCI Patients from Semantically Parcelled PET Images: A Comparison between AV45 and FDG-PETSeyed Hossein Nozadi, Samuel Kadoury, Alzheimer's Disease Neuroimaging Initiative. ijbi, 2018, 2018. [doi]

Standardized quality metric system for structural brain magnetic resonance images in multi-center neuroimaging studyMichael Osadebey, Marius Pedersen, Douglas L. Arnold, Katrina Wendel-Mitoraj, Alzheimer's Disease Neuroimaging Initiative. bmcmi, 18(1), 2018. [doi]

Analysis of ordinal longitudinal data under nonignorable missingness and misreporting: An application to Alzheimer's disease studySubrata Rana, Surupa Roy, Kalyan Das, Alzheimer's Disease Neuroimaging Initiative. ma, 166:62-77, 2018. [doi]

Learning non-linear patch embeddings with neural networks for label fusionGerard Sanroma, Oualid M. Benkarim, Gemma Piella, Oscar Camara, Guorong Wu 0001, Dinggang Shen, Juan Domingo Gispert, José Luis Molinuevo, Miguel Ángel González Ballester, Alzheimer's Disease Neuroimaging Initiative. mia, 44:143-155, 2018. [doi]

Integrating spatial-anatomical regularization and structure sparsity into SVM: Improving interpretation of Alzheimer's disease classificationZhuo Sun, Yuchuan Qiao, Boudewijn P. F. Lelieveldt, Marius Staring, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 178:445-460, 2018. [doi]

The EADC-ADNI harmonized protocol for hippocampal segmentation: A validation studyAzar Zandifar, Vladimir S. Fonov, Jens C. Pruessner, D. Louis Collins, Alzheimer's Disease Neuroimaging Initiative. neuroimage, 181:142-148, 2018. [doi]

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