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Anees Abrol
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2020 – today
- 2024
- [j9]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]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]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]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]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]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 - [i7]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) - [i6]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) - [i5]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) - [i4]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) - 2023
- [c21]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]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]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]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]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]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]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]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]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]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]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]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]Ishaan Batta, Anees Abrol, Zening Fu, Vince D. Calhoun:
Learning Active Multimodal Subspaces in the Brain. EMBC 2022: 3822-3825 - [i2]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]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]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]Anees Abrol, Reihaneh Hassanzadeh, Sergey M. Plis, Vince D. Calhoun
:
Deep learning in resting-state fMRI*. EMBC 2021: 3965-3969 - [c10]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]Ishaan Batta, Anees Abrol, Zening Fu, Vince D. Calhoun
:
Varying Information Complexity in Functional Domain Interactions in Schizophrenia. BIBE 2020: 1042-1047 - [c8]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]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
- 2019
- [j2]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]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]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]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]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]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]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]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]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
Coauthor Index
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last updated on 2024-09-10 02:09 CEST by the dblp team
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