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2020 – today

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2024
[j9]
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Zening Fu, Ishaan Batta, Lei Wu, Anees Abrol, Oktay Agcaoglu, Mustafa S. Salman, Yuhui Du, Armin Iraji, Sarah Shultz, Jing Sui, Vince D. Calhoun:
Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities. NeuroImage 292: 120617 (2024)
[j8]
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Yuda Bi, Anees Abrol, Sihan Jia, Jing Sui, Vince D. Calhoun:
Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity. NeuroImage 297: 120674 (2024)
[j7]
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Sahithi Kolla, Haleh Falakshahi, Anees Abrol, Zening Fu, Vince D. Calhoun:
Intra-Atlas Node Size Effects on Graph Metrics in fMRI Data: Implications for Alzheimer's Disease and Cognitive Impairment. Sensors 24(3): 814 (2024)
[c24]
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Ishaan Batta, Anees Abrol, Vince D. Calhoun:
A Novel Deep Subspace Learning Framework to Automatically Uncover Assessment-Specific Independent Brain Networks. CISS 2024: 1-6
[c23]
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Yuda Bi, Anees Abrol, Jing Sui, Vince D. Calhoun:
Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs. ICASSP 2024: 1756-1760
[c22]
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Vaibhavi S. Itkyal, Anees Abrol, Theodore J. LaGrow, Vince D. Calhoun:
Voxelwise Intensity Projection for the Spatial Representation of Resting State Functional MRI Networks and Multimodal Deep Learning. ISBI 2024: 1-4
[i8]
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  - journals/corr/abs-2405-05462
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Reihaneh Hassanzadeh, Anees Abrol, Hamid Reza Hassanzadeh, Vince D. Calhoun:
Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer's Disease Biomarkers. CoRR abs/2405.05462 (2024)
[i7]
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  - journals/corr/abs-2406-13292
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Giorgio Dolci, Federica Cruciani, Md Abdur Rahaman, Anees Abrol, Jiayu Chen, Zening Fu, Ilaria Boscolo Galazzo, Gloria Menegaz, Vince D. Calhoun:
An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease. CoRR abs/2406.13292 (2024)
[i6]
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  - journals/corr/abs-2406-13305
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Giorgio Dolci, Charles A. Ellis, Federica Cruciani, Lorenza Brusini, Anees Abrol, Ilaria Boscolo Galazzo, Gloria Menegaz, Vince D. Calhoun:
Multimodal MRI-based Detection of Amyloid Status in Alzheimer's Disease Continuum. CoRR abs/2406.13305 (2024)
[i5]
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  - journals/corr/abs-2408-00378
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Yuxiang Wei, Anees Abrol, James J. Lah, Deqiang Qiu, Vince D. Calhoun:
A deep spatio-temporal attention model of dynamic functional network connectivity shows sensitivity to Alzheimer's in asymptomatic individuals. CoRR abs/2408.00378 (2024)
[i4]
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  - journals/corr/abs-2408-13074
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Yuxiang Wei, Anees Abrol, Reihaneh Hassanzadeh, Vince D. Calhoun:
Hierarchical Spatio-Temporal State-Space Modeling for fMRI Analysis. CoRR abs/2408.13074 (2024)
2023
[c21]
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Giorgio Dolci, Md Abdur Rahaman, Ilaria Boscolo Galazzo, Federica Cruciani, Anees Abrol, Jiayu Chen, Zening Fu, Kuaikuai Duan, Gloria Menegaz, Vince D. Calhoun:
Deep Generative Transfer Learning Predicts Conversion To Alzheimer'S Disease From Neuroimaging Genomics Data. ICASSP Workshops 2023: 1-5
[c20]
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Ishaan Batta, Anees Abrol, Vince D. Calhoun:
A Multimodal Deep Learning Approach for Automated Detection and Characterization of Distinctly Salient Features of Alzheimers Disease. ISBI 2023: 1-4
[c19]
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Yuda Bi, Anees Abrol, Zening Fu, Vince D. Calhoun:
MultiViT: Multimodal Vision Transformer for Schizophrenia Prediction using Structural MRI and Functional Network Connectivity Data. ISBI 2023: 1-5
[i3]
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  - journals/corr/abs-2309-08160
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Yuda Bi, Anees Abrol, Jing Sui, Vince D. Calhoun:
Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs. CoRR abs/2309.08160 (2023)
2022
[j6]
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Mustafa S. Salman, Tor D. Wager, Eswar Damaraju, Anees Abrol, Victor M. Vergara, Zening Fu, Vince D. Calhoun:
An Approach to Automatically Label and Order Brain Activity/Component Maps. Brain Connect. 12(1): 85-95 (2022)
[j5]
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Ishaan Batta, Anees Abrol, Zening Fu, Adrian Preda, Theo G. M. van Erp, Vince D. Calhoun:
Building Models of Functional Interactions Among Brain Domains that Encode Varying Information Complexity: A Schizophrenia Case Study. Neuroinformatics 20(3): 777-791 (2022)
[j4]
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Weizheng Yan, Gang Qu, Wenxing Hu, Anees Abrol, Biao Cai, Chen Qiao, Sergey M. Plis, Yu-Ping Wang, Jing Sui, Vince D. Calhoun:
Deep Learning in Neuroimaging: Promises and challenges. IEEE Signal Process. Mag. 39(2): 87-98 (2022)
[c18]
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  - conf/bhi/HassanzadehAC22
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Reihaneh Hassanzadeh, Anees Abrol, Vince D. Calhoun:
Classification of Schizophrenia and Alzheimer's Disease using Resting-State Functional Network Connectivity. BHI 2022: 1-4
[c17]
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Giorgio Dolci, Md Abdur Rahaman, Jiayu Chen, Kuaikuai Duan, Zening Fu, Anees Abrol, Gloria Menegaz, Vince D. Calhoun:
A deep generative multimodal imaging genomics framework for Alzheimer's disease prediction. BIBE 2022: 41-44
[c16]
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Anees Abrol, Vince D. Calhoun:
Discovery and Replication of Time-Resolved Functional Network Connectivity Differences in Adolescence and Adulthood in over 50K fMRI Datasets. EMBC 2022: 1855-1858
[c15]
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Anees Abrol, Ihab Hajjar, Vince D. Calhoun:
Probing the link between the APOE-ε4 allele and whole-brain gray matter using deep learning. EMBC 2022: 3506-3509
[c14]
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Yuda Bi, Anees Abrol, Zening Fu, Vince D. Calhoun:
Deep Learning Prediction and Visualization of Gender Related Brain Changes from Longitudinal Structural MRI Data in the ABCD Study. EMBC 2022: 3814-3817
[c13]
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Ishaan Batta, Anees Abrol, Zening Fu, Vince D. Calhoun:
Learning Active Multimodal Subspaces in the Brain. EMBC 2022: 3822-3825
[i2]
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  - journals/corr/abs-2208-12909
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Xinhui Li, Alex Fedorov, Mrinal Mathur, Anees Abrol, Gregory Kiar, Sergey M. Plis, Vince D. Calhoun:
Pipeline-Invariant Representation Learning for Neuroimaging. CoRR abs/2208.12909 (2022)
2021
[j3]
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Debbrata K. Saha, Eswar Damaraju, Barnaly Rashid, Anees Abrol, Sergey M. Plis, Vince D. Calhoun:
A Classification-Based Approach to Estimate the Number of Resting Functional Magnetic Resonance Imaging Dynamic Functional Connectivity States. Brain Connect. 11(2): 132-145 (2021)
[c12]
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Ishaan Batta, Anees Abrol, Vince D. Calhoun:
Uncovering Active Structural Subspaces Associated with Changes in Indicators for Alzheimer's Disease. EMBC 2021: 3948-3951
[c11]
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Anees Abrol, Reihaneh Hassanzadeh, Sergey M. Plis, Vince D. Calhoun:
Deep learning in resting-state fMRI^*. EMBC 2021: 3965-3969
[c10]
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Ishaan Batta, Anees Abrol, Zening Fu, Vince D. Calhoun:
A Multimodal Learning Framework to Study Varying Information Complexity in Structural and Functional Sub-Domains in Schizophrenia. ISBI 2021: 994-998
2020
[c9]
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Ishaan Batta, Anees Abrol, Zening Fu, Vince D. Calhoun:
Varying Information Complexity in Functional Domain Interactions in Schizophrenia. BIBE 2020: 1042-1047
[c8]
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Mustafa S. Salman, Tor D. Wager, Eswar Damaraju, Anees Abrol, Vince D. Calhoun:
Fully automated ordering and labeling of ICA components. BIBM 2020: 1110-1114
[c7]
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  - conf/isbi/IrajiLFFDAQC20
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Armin Iraji, Noah Lewis, Ashkan Faghiri, Zening Fu, Thomas DeRamus, Anees Abrol, Shile Qi, Vince D. Calhoun:
Functional Multi-Connectivity: A Novel Approach To Assess Multi-Way Entanglement Between Networks and Voxels. ISBI 2020: 1698-1701

2010 – 2019

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2019
[j2]
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Bradley T. Baker, Anees Abrol, Rogers F. Silva, Eswar Damaraju, Anand D. Sarwate, Vince D. Calhoun, Sergey M. Plis:
Decentralized temporal independent component analysis: Leveraging fMRI data in collaborative settings. NeuroImage 186: 557-569 (2019)
[c6]
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Alex Fedorov, R. Devon Hjelm, Anees Abrol, Zening Fu, Yuhui Du, Sergey M. Plis, Vince D. Calhoun:
Prediction of Progression to Alzheimer's disease with Deep InfoMax. BHI 2019: 1-5
[c5]
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Victor M. Vergara, Anees Abrol, Flor A. Espinoza, Vince D. Calhoun:
Selection of Efficient Clustering Index to Estimate the Number of Dynamic Brain States from Functional Network Connectivity. EMBC 2019: 632-635
[c4]
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Anees Abrol, Hooman Rokham, Vince D. Calhoun:
Diagnostic and Prognostic Classification of Brain Disorders Using Residual Learning on Structural MRI Data. EMBC 2019: 4084-4088
[c3]
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Anees Abrol, Zening Fu, Yuhui Du, Vince D. Calhoun:
Multimodal Data Fusion of Deep Learning and Dynamic Functional Connectivity Features to Predict Alzheimer's Disease Progression. EMBC 2019: 4409-4413
[c2]
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Debbrata K. Saha, Anees Abrol, Eswar Damaraju, Barnaly Rashid, Sergey M. Plis, Vince D. Calhoun:
Classification As a Criterion to Select Model Order For Dynamic Functional Connectivity States in Rest-fMRI Data. ISBI 2019: 1602-1605
[i1]
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  - journals/corr/abs-1904-10931
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Alex Fedorov, R. Devon Hjelm, Anees Abrol, Zening Fu, Yuhui Du, Sergey M. Plis, Vince D. Calhoun:
Prediction of Progression to Alzheimer's disease with Deep InfoMax. CoRR abs/1904.10931 (2019)
2017
[j1]
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Anees Abrol, Eswar Damaraju, Robyn L. Miller, Julia M. Stephen, Eric D. Claus, Andrew R. Mayer, Vince D. Calhoun:
Replicability of time-varying connectivity patterns in large resting state fMRI samples. NeuroImage 163: 160-176 (2017)
2016
[c1]
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Anees Abrol, Charlotte Chaze, Eswar Damaraju, Vince D. Calhoun:
The chronnectome: Evaluating replicability of dynamic connectivity patterns in 7500 resting fMRI datasets. EMBC 2016: 5571-5574

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