20.9.7.5 Functional Magnetic Resonance, fMRI

Seghouane, A.K., Iqbal, A.,
Sequential Dictionary Learning From Correlated Data: Application to fMRI Data Analysis,
IP(26), No. 6, June 2017, pp. 3002-3015.
IEEE DOI 1705
Algorithm design and analysis, Approximation algorithms, Brain modeling, Correlation, Data analysis, Dictionaries, Image coding, Functional magnetic resonance imaging (fMRI), correlation, dictionary learning, regularization, sequential update, sparsity
See also Approach for Sequential Dictionary Learning in Nonuniform Noise, An. BibRef

Seghouane, A.K., Iqbal, A.,
Basis Expansion Approaches for Regularized Sequential Dictionary Learning Algorithms With Enforced Sparsity for fMRI Data Analysis,
MedImg(36), No. 9, September 2017, pp. 1796-1807.
IEEE DOI 1709
BibRef
And:
Learning dictionaries from correlated data: Application to fMRI data analysis,
ICIP16(2340-2344)
IEEE DOI 1610
biomedical MRI, data analysis, medical signal processing, basis expansion approach, classical dictionary learning algorithm, fMRI data analysis, functional magnetic resonance imaging, learned dictionary atom, BibRef

Seghouane, A.K., Iqbal, A.,
CSMSDL: A common sequential dictionary learning algorithm for multi-subject FMRI data sets analysis,
ICIP17(4113-4117)
IEEE DOI 1803
biomedical MRI, data analysis, medical image processing, CSMSDL, common sequential dictionary learning algorithm, sparsity BibRef

Hu, C., Reeves, S., Peters, D.C., Twieg, D.,
An Efficient Reconstruction Algorithm Based on the Alternating Direction Method of Multipliers for Joint Estimation of R_2^* and Off-Resonance in fMRI,
MedImg(36), No. 6, June 2017, pp. 1326-1336.
IEEE DOI 1706
Cost function, Data models, Image reconstruction, Imaging, Nonlinear distortion, Trajectory, ADMM, BOLD fMRI, geometric distortion, rosette BibRef

Bolton, T.A.W., Tarun, A., Sterpenich, V., Schwartz, S., van de Ville, D.,
Interactions Between Large-Scale Functional Brain Networks are Captured by Sparse Coupled HMMs,
MedImg(37), No. 1, January 2018, pp. 230-240.
IEEE DOI 1801
biomedical MRI, brain, deconvolution, hidden Markov models, medical image processing, complex temporal dynamics, total activation BibRef

Olafsson, V.T., Noll, D.C., Fessler, J.A.,
Fast Spatial Resolution Analysis of Quadratic Penalized Least-Squares Image Reconstruction With Separate Real and Imaginary Roughness Penalty: Application to fMRI,
MedImg(37), No. 2, February 2018, pp. 604-614.
IEEE DOI 1802
Cost function, Discrete Fourier transforms, Image reconstruction, Spatial resolution, Localimpulse response, functional MRI (fMRI), separate real and imaginary regularization BibRef

Wettenhovi, V.V.[Ville-Veikko], Kolehmainen, V.[Ville], Huttunen, J.[Joanna], Kettunen, M.[Mikko], Gröhn, O.[Olli], Vauhkonen, M.[Marko],
State Estimation with Structural Priors in fMRI,
JMIV(60), No. 2, February 2018, pp. 174-188.
Springer DOI 1802
BibRef

Fang, J., Xu, C., Zille, P., Lin, D., Deng, H.W., Calhoun, V.D., Wang, Y.P.,
Fast and Accurate Detection of Complex Imaging Genetics Associations Based on Greedy Projected Distance Correlation,
MedImg(37), No. 4, April 2018, pp. 860-870.
IEEE DOI 1804
Computational efficiency, Correlation, Genetics, Neuroimaging, Testing, Imaging genetics, SNP, distance correlation, fMRI, projected distance correlation BibRef

Huang, W., Bolton, T.A.W., Medaglia, J.D., Bassett, D.S., Ribeiro, A., van de Ville, D.,
A Graph Signal Processing Perspective on Functional Brain Imaging,
PIEEE(106), No. 5, May 2018, pp. 868-885.
IEEE DOI 1805
Adaptive systems, Brain modeling, Extraterrestrial measurements, Graph theory, Magnetic resonance imaging, Neuroimaging, neuroimaging BibRef

Huang, H., Hu, X., Zhao, Y., Makkie, M., Dong, Q., Zhao, S., Guo, L., Liu, T.,
Modeling Task fMRI Data Via Deep Convolutional Autoencoder,
MedImg(37), No. 7, July 2018, pp. 1551-1561.
IEEE DOI 1808
biomedical MRI, brain, independent component analysis, learning (artificial intelligence), medical image processing, unsupervised BibRef

Seghouane, A., Shokouhi, N.,
Consistent Estimation of Dimensionality for Data-Driven Methods in fMRI Analysis,
MedImg(38), No. 2, February 2019, pp. 493-503.
IEEE DOI 1902
Functional magnetic resonance imaging, Eigenvalues and eigenfunctions, Covariance matrices, Data models, ICA BibRef

Wang, H.[Han], Zhao, S.J.[Shi-Jie], Dong, Q.L.[Qing-Lin], Cui, Y.[Yan], Chen, Y.W.[Yao-Wu], Han, J.W.[Jun-Wei], Xie, L.[Li], Liu, T.M.[Tian-Ming],
Recognizing Brain States Using Deep Sparse Recurrent Neural Network,
MedImg(38), No. 4, April 2019, pp. 1058-1068.
IEEE DOI 1904
Task analysis, Brain modeling, Recurrent neural networks, Functional magnetic resonance imaging, Logic gates, Data models, brain networks BibRef

Zhao, S.J.[Shi-Jie], Cui, Y.[Yan], Chen, Y.W.[Yao-Wu], Zhang, X.[Xin], Zhang, W.[Wei], Liu, H.[Huan], Han, J.W.[Jun-Wei], Guo, L.[Lei], Xie, L.[Li], Liu, T.M.[Tian-Ming],
Exploring Brain Hemodynamic Response Patterns via Deep Recurrent Autoencoder,
MBIA19(66-74).
Springer DOI 1912
BibRef

Bhinge, S., Mowakeaa, R., Calhoun, V.D., Adali, T.,
Extraction of Time-Varying Spatiotemporal Networks Using Parameter-Tuned Constrained IVA,
MedImg(38), No. 7, July 2019, pp. 1715-1725.
IEEE DOI 1907
Functional magnetic resonance imaging, Feature extraction, Estimation, Data models, Adaptation models, fMRI analysis BibRef

Raut, Y.[Yudhishthir], Gamad, R.S., Bansod, P.P.,
Objective analysis and bit rate analysis of HEVC compressed 4D-fMRI images,
IJIST(29), No. 3, September 2019, pp. 283-296.
DOI Link 1908
BibRef

Liao, W., Li, J., Ji, G., Wu, G., Long, Z., Xu, Q., Duan, X., Cui, Q., Biswal, B.B., Chen, H.,
Endless Fluctuations: Temporal Dynamics of the Amplitude of Low Frequency Fluctuations,
MedImg(38), No. 11, November 2019, pp. 2523-2532.
IEEE DOI 1911
Functional magnetic resonance imaging, Brain, Time series analysis, Fluctuations, Neuromodulation, temporal dynamics BibRef

Hourani, O.[Osama], Charkari, N.M.[Nasrollah Moghadam], Jalili, S.[Saeed],
Voxel selection framework based on meta-heuristic search and mutual information for brain decoding,
IJIST(29), No. 4, 2019, pp. 663-676.
DOI Link 1911
classification, computer heuristics, functional magnetic resonance imaging, information theory, voxel selection BibRef

Ruttorf, M., Kristensen, S., Schad, L.R., Almeida, J.,
Transcranial Direct Current Stimulation Alters Functional Network Structure in Humans: A Graph Theoretical Analysis,
MedImg(38), No. 12, December 2019, pp. 2829-2837.
IEEE DOI 1912
Tools, Functional magnetic resonance imaging, Electronics packaging, Brain, Task analysis, transcranial direct current stimulation BibRef

Almodóvar-Rivera, I., Maitra, R.,
Fast Adaptive Smoothing and Thresholding for Improved Activation Detection in Low-Signal fMRI,
MedImg(38), No. 12, December 2019, pp. 2821-2828.
IEEE DOI 1912
Smoothing methods, Thresholding (Imaging), Functional magnetic resonance imaging, Correlation, Limiting, TFCE BibRef

Wang, T.[Ting], Wu, X.[Xi], Jiang, J.[Jiefeng], Liu, C.[Chang], Zhu, M.[Ming],
Functional neural interactions during adaptive reward learning: An functional magnetic resonance imaging study,
IJIST(30), No. 1, 2020, pp. 92-103.
DOI Link 2002
adaptive reward learning, functional magnetic resonance imaging, learning rate, psychophysiological interaction analysis BibRef

Gupta, K.O., Chatur, P.N.,
Gradient self-weighting linear collaborative discriminant regression classification for human cognitive states classification,
MVA(31), No. 3, March 2020, pp. Article21.
Springer DOI 2004
BibRef

Kuang, L., Lin, Q., Gong, X., Cong, F., Wang, Y., Calhoun, V.D.,
Shift-Invariant Canonical Polyadic Decomposition of Complex-Valued Multi-Subject fMRI Data With a Phase Sparsity Constraint,
MedImg(39), No. 4, April 2020, pp. 844-853.
IEEE DOI 2004
Functional magnetic resonance imaging, Delay effects, Frequency-domain analysis, Data models, Spatiotemporal phenomena, spatiotemporal constraints BibRef

Sauvage, J., Porée, J., Rabut, C., Férin, G., Flesch, M., Rosinski, B., Nguyen-Dinh, A., Tanter, M., Pernot, M., Deffieux, T.,
4D Functional Imaging of the Rat Brain Using a Large Aperture Row-Column Array,
MedImg(39), No. 6, June 2020, pp. 1884-1893.
IEEE DOI 2006
3D flow imaging, functional imaging, matrix array, ultrafast ultrasound BibRef

Huang, J., Zhou, L., Wang, L., Zhang, D.,
Attention-Diffusion-Bilinear Neural Network for Brain Network Analysis,
MedImg(39), No. 7, July 2020, pp. 2541-2552.
IEEE DOI 2007
Functional magnetic resonance imaging, Diffusion tensor imaging, Feature extraction, epilepsy BibRef

Kassani, P.H.[P. Hosseinzadeh], Xiao, L., Zhang, G., Stephen, J.M., Wilson, T.W., Calhoun, V.D., Wang, Y.P.,
Causality-Based Feature Fusion for Brain Neuro-Developmental Analysis,
MedImg(39), No. 11, November 2020, pp. 3290-3299.
IEEE DOI 2011
Functional magnetic resonance imaging, Brain modeling, Feature extraction, Time series analysis, History, Correlation, polynomial neural network BibRef

Hu, D., Zhang, H., Wu, Z., Wang, F., Wang, L., Smith, J.K., Lin, W., Li, G., Shen, D.,
Disentangled-Multimodal Adversarial Autoencoder: Application to Infant Age Prediction With Incomplete Multimodal Neuroimages,
MedImg(39), No. 12, December 2020, pp. 4137-4149.
IEEE DOI 2012
Functional magnetic resonance imaging, Brain modeling, Predictive models, Data models, Biological system modeling, magnetic resonance imaging BibRef

Guo, S., Fessler, J.A., Noll, D.C.,
High-Resolution Oscillating Steady-State fMRI Using Patch-Tensor Low-Rank Reconstruction,
MedImg(39), No. 12, December 2020, pp. 4357-4368.
IEEE DOI 2012
Tensors, Functional magnetic resonance imaging, Image reconstruction, Signal to noise ratio, Oscillators, prospective undersampling BibRef

Lin, Q.A.[Qi-Ang], Man, Z.X.[Zheng-Xing], Cao, Y.C.[Yong-Chun], Deng, T.[Tao], Han, C.C.[Cheng-Cheng], Cao, C.G.[Chuan-Gui], Zhang, L.J.[Lin-Jun], Zeng, S.[Sitao], Gao, R.T.[Rui-Ting], Wang, W.[Weilan], Ji, J.S.[Jin-Shui], Huang, X.D.[Xiao-Di],
Classifying functional nuclear images with convolutional neural networks: A survey,
IET-IPR(14), No. 14, December 2020, pp. 3300-3313.
DOI Link 2012
Survey, Nuclear Imaging. BibRef

Sen, B., Parhi, K.K.,
Graph-Theoretic Properties of Sub-Graph Entropy,
SPLetters(28), 2021, pp. 135-139.
IEEE DOI 2101
Entropy, Measurement, Functional magnetic resonance imaging, Noise measurement, Upper bound, Task analysis, Stability criteria, sub-graph entropy BibRef

Zhang, J.J.[Jian-Jia], Wang, L.[Lei], Zhou, L.P.[Lu-Ping], Li, W.Q.[Wan-Qing],
Beyond Covariance: SICE and Kernel Based Visual Feature Representation,
IJCV(129), No. 2, February 2021, pp. 300-320.
Springer DOI 2102
BibRef
And: A1, A3, A2, A4:
Exploring Compact Representation of SICE Matrices for Functional Brain Network Classification,
MLMI14(59-67).
Springer DOI 1410
BibRef

Wang, L.[Lei], Zhang, J.J.[Jian-Jia], Zhou, L.P.[Lu-Ping], Tang, C., Li, W.Q.[Wan-Qing],
Beyond Covariance: Feature Representation with Nonlinear Kernel Matrices,
ICCV15(4570-4578)
IEEE DOI 1602
Computer vision BibRef

Ting, C.M., Samdin, S.B., Tang, M., Ombao, H.,
Detecting Dynamic Community Structure in Functional Brain Networks Across Individuals: A Multilayer Approach,
MedImg(40), No. 2, February 2021, pp. 468-480.
IEEE DOI 2102
Nonhomogeneous media, Hidden Markov models, Task analysis, Brain modeling, Switches, Functional magnetic resonance imaging, fMRI BibRef

Chen, C.M.[Chun-Ming], Yang, H.C.[Hui-Chieh], Hsieh, H.H.[Hsin-Hua], Liao, T.Y.[Tsai-Ying], Huang, Y.C.[Yen-Chih], Peng, S.L.[Shin-Lei],
Characterization of regional differences in cerebral vascular response to breath holding using BOLD fMRI,
IJIST(31), No. 1, 2021, pp. 180-188.
DOI Link 2102
autoregulation, cerebral blood flow, hypercapnia, reactivity, sex BibRef

Bai, Y., Gong, Y., Bai, J., Liu, J., Deng, H.W., Calhoun, V., Wang, Y.P.,
A Joint Analysis of Multi-Paradigm fMRI Data With Its Application to Cognitive Study,
MedImg(40), No. 3, March 2021, pp. 951-962.
IEEE DOI 2103
Functional magnetic resonance imaging, Collaboration, Task analysis, Data models, Correlation, Imaging, Feature extraction, feature selection BibRef

Wu, H.[Hui], Wang, J.[Jianjia], Hancock, E.R.[Edwin R.],
fMRI Brain Networks as Statistical Mechanical Ensembles,
ICPR21(1694-1700)
IEEE DOI 2105
Temperature distribution, Microscopy, Time series analysis, Functional magnetic resonance imaging, Tools, Entropy, Energy states BibRef

Deairmendereli, G.G.[Gonul Gunal], Vural, F.T.Y.[Fatos T. Yarman],
Estimating Static and Dynamic Brain Networks by Kulback-Leibler Divergence from fMRI Data,
ICPR21(5913-5919)
IEEE DOI 2105
Support vector machines, Analytical models, Computational modeling, Functional magnetic resonance imaging, Tower of London BibRef

Taneja, K.[Karan], Kulkarni, P.H.[Prachi H.], Merchant, S.N., Awate, S.P.[Suyash P.],
A Bayesian Deep CNN Framework for Reconstructing k-t-Undersampled Resting-fMRI,
ICPR21(8492-8499)
IEEE DOI 2105
Uncertainty, Frequency-domain analysis, Memory management, Nonhomogeneous media, Bayes methods, Spatiotemporal phenomena, uncertainty BibRef