21.9 Medical Applications -- Brain, Cortex Applications

Hughes, N.J., Goodhill, G.J.,
Estimating Cortical Feature Maps with Dependent Gaussian Processes,
PAMI(39), No. 10, October 2017, pp. 1918-1928.
IEEE DOI 1709
Covariance matrices, Gaussian processes, Image reconstruction, Imaging, Kernel, Noise measurement, Visualization, Gaussian processes, multitask learning, neuroimaging, visual cortical maps BibRef

Huang, J.Y., Hughes, N.J., Goodhill, G.J.,
Segmenting Neuronal Growth Cones Using Deep Convolutional Neural Networks,
DICTA16(1-7)
IEEE DOI 1701
Axons BibRef

Lopes, P., Baudisch, P.,
Interactive Systems Based on Electrical Muscle Stimulation,
Computer(50), No. 10, 2017, pp. 28-35.
IEEE DOI 1710
electromyography, interactive systems, muscle, EMS, electrical muscle stimulation, guided training, immersive virtual experiences, information access, interactive systems, mechanical actuation, BibRef

Zeng, D., Xie, Q., Cao, W., Lin, J., Zhang, H., Zhang, S., Huang, J., Bian, Z., Meng, D., Xu, Z., Liang, Z., Chen, W., Ma, J.,
Low-Dose Dynamic Cerebral Perfusion Computed Tomography Reconstruction via Kronecker-Basis-Representation Tensor Sparsity Regularization,
MedImg(36), No. 12, December 2017, pp. 2546-2556.
IEEE DOI 1712
Biomedical imaging, Brain modeling, Computed tomography, Correlation, Image reconstruction, Tensile stress, tensor BibRef

Li, S.[Sui], Zeng, D.[Dong], Peng, J.J.[Jiang-Jun], Bian, Z.Y.[Zhao-Ying], Zhang, H.[Hao], Xie, Q.[Qi], Wang, Y.B.[Yong-Bo], Liao, Y.T.[Yu-Ting], Zhang, S.L.[Shan-Li], Huang, J.[Jing], Meng, D.Y.[De-Yu], Xu, Z.B.[Zong-Ben], Ma, J.H.[Jian-Hua],
An Efficient Iterative Cerebral Perfusion CT Reconstruction via Low-Rank Tensor Decomposition With Spatial-Temporal Total Variation Regularization,
MedImg(38), No. 2, February 2019, pp. 360-370.
IEEE DOI 1902
Tensile stress, Image reconstruction, Hemodynamics, Matrix decomposition, Numerical models, Computed tomography, regularization BibRef

Masood, S.[Saleha], Sheng, B.[Bin], Li, P.[Ping], Shen, R.M.[Rui-Min], Fang, R.G.[Ruo-Gu], Wu, Q.A.[Qi-Ang],
Automatic choroid layer segmentation using normalized graph cut,
IET-IPR(12), No. 1, January 2018, pp. 53-59.
DOI Link 1712
BibRef

Li, L.L.[Liang-Liang], Si, Y.J.[Yu-Juan], Jia, Z.H.[Zhen-Hong],
A novel brain image enhancement method based on nonsubsampled contourlet transform,
IJIST(28), No. 2, 2018, pp. 124-131.
WWW Link. 1806
BibRef

Chitra, S., Kumaratharan, N., Ramesh, S.,
Enhanced brain image retrieval using carrier frequency offset compensated orthogonal frequency division multiplexing for telemedicine applications,
IJIST(28), No. 3, September 2018, pp. 186-195.
WWW Link. 1808
BibRef

Mondal, P.[Prasenjit], Bhowmick, P.[Partha], Mukherjee, J.[Jayanta], Sural, S.[Shamik],
Efficient computation of cross-sections from human brain model by geometric processing,
RealTimeIP(15), No. 2, August 2018, pp. 421-434.
Springer DOI 1808
BibRef

Zhang, D., Huang, J., Jie, B., Du, J., Tu, L., Liu, M.,
Ordinal Pattern: A New Descriptor for Brain Connectivity Networks,
MedImg(37), No. 7, July 2018, pp. 1711-1722.
IEEE DOI 1808
biomedical MRI, brain, diseases, feature extraction, image classification, learning (artificial intelligence), regression BibRef

Zia, R.[Razia], Akhtar, P.[Pervez], Aziz, A.[Arshad],
A new rectangular window based image cropping method for generalization of brain neoplasm classification systems,
IJIST(28), No. 3, September 2018, pp. 153-162.
WWW Link. 1808
BibRef

Lyu, I.[Ilwoo], Kim, S.H.[Sun Hyung], Woodward, N.D.[Neil D.], Styner, M.A.[Martin A.], Landman, B.A.[Bennett A.],
TRACE: A Topological Graph Representation for Automatic Sulcal Curve Extraction,
MedImg(37), No. 7, July 2018, pp. 1653-1663.
IEEE DOI 1808
Cortex. data acquisition, feature extraction, image reconstruction, image registration, medical image processing, valley detection BibRef

Ning, L., Rathi, Y.,
A Dynamic Regression Approach for Frequency-Domain Partial Coherence and Causality Analysis of Functional Brain Networks,
MedImg(37), No. 9, September 2018, pp. 1957-1969.
IEEE DOI 1809
Correlation, Frequency-domain analysis, Time series analysis, Entropy, Coherence, Standards, Causality, coherence, frequency, simulation BibRef

Hazarika, A.[Anil], Dutta, L.[Lachit], Boro, M.[Meenakshi], Barthakur, M.[Mausumi], Bhuyan, M.[Manabendra],
An automatic feature extraction and fusion model: Application to electromyogram (EMG) signal classification,
MultInfoRetr(8), No. 3, September 2018, pp. 173-186.
Springer DOI 1809
BibRef

Zille, P., Calhoun, V.D., Wang, Y.,
Enforcing Co-Expression Within a Brain-Imaging Genomics Regression Framework,
MedImg(37), No. 12, December 2018, pp. 2561-2571.
IEEE DOI 1812
Bioinformatics, Genomics, Imaging, Feature extraction, Correlation, Data models, Data integration, biomedical signal processing, signal representation BibRef

Baselice, F., Sorriso, A., Rucco, R., Sorrentino, P.,
Phase Linearity Measurement: A Novel Index for Brain Functional Connectivity,
MedImg(38), No. 4, April 2019, pp. 873-882.
IEEE DOI 1904
Phase measurement, Synchronization, Oscillators, Correlation, Indexes, Brain, Brain functional connectivity, functional coupling, volume conduction BibRef

Ma, M.[Ming], Wang, X.[Xu], Duan, Y.[Ye], Frey, S.H.[Scott H.], Gu, X.F.[Xian-Feng],
Optimal mass transport based brain morphometry for patients with congenital hand deformities,
VC(35), No. 9, September 2018, pp. 1311-1325.
WWW Link. 1908
BibRef

Pang, S., Lu, Z., Jiang, J., Zhao, L., Lin, L., Li, X., Lian, T., Huang, M., Yang, W., Feng, Q.,
Hippocampus Segmentation Based on Iterative Local Linear Mapping With Representative and Local Structure-Preserved Feature Embedding,
MedImg(38), No. 10, October 2019, pp. 2271-2280.
IEEE DOI 1910
Manifolds, Image segmentation, Hippocampus, Dictionaries, Image reconstruction, Diseases, Training, Deep learning, manifold regularization BibRef

Shen, L., Thompson, P.M.,
Brain Imaging Genomics: Integrated Analysis and Machine Learning,
PIEEE(108), No. 1, January 2020, pp. 125-162.
IEEE DOI 2001
Genomics, Bioinformatics, Brain modeling, Machine learning, Biomedical imaging, Big data, brain imaging, genomics, statistics BibRef

Zhang, G., Cai, B., Zhang, A., Stephen, J.M., Wilson, T.W., Calhoun, V.D., Wang, Y.,
Estimating Dynamic Functional Brain Connectivity With a Sparse Hidden Markov Model,
MedImg(39), No. 2, February 2020, pp. 488-498.
IEEE DOI 2002
Uniform resource locators, Bibliographies, Standards, Documentation, Databases, Sorting, Memory management, brain development BibRef

Jose, S.[Shobha], George, S.T.[S. Thomas], Roopchand, P.S.,
DWT-based electromyogram signal classification using maximum likelihood-estimated features for neurodiagnostic applications,
SIViP(14), No. 3, April 2020, pp. 601-608.
WWW Link. 2004
BibRef

Kaur, T.[Taranjit], Gandhi, T.K.[Tapan Kumar],
Deep convolutional neural networks with transfer learning for automated brain image classification,
MVA(31), No. 3, March 2020, pp. Article20.
Springer DOI 2004
BibRef

CHAN, H.L.[Hei Long], YAM, T.C.[Tsz Chun], LUI, L.M.[Lok Ming],
Automatic characteristic-calibrated registration (ACC-REG): Hippocampal surface registration using eigen-graphs,
PR(103), 2020, pp. 107142.
Elsevier DOI 2005
Feature extraction, Feature correspondence, Surface registration, Surface deformation, Eigen-graph BibRef

Huang, S., Lyu, I., Qiu, A., Chung, M.K.,
Fast Polynomial Approximation of Heat Kernel Convolution on Manifolds and Its Application to Brain Sulcal and Gyral Graph Pattern Analysis,
MedImg(39), No. 6, June 2020, pp. 2201-2212.
IEEE DOI 2006
Heat diffusion, Laplace-Beltrami operator, brain cortical sulcal curves, diffusion wavelets, Chebyshev polynomials BibRef

Tang, Z., Liu, X., Li, Y., Yap, P., Shen, D.,
Multi-Atlas Brain Parcellation Using Squeeze-and-Excitation Fully Convolutional Networks,
IP(29), 2020, pp. 6864-6872.
IEEE DOI 2007
Brain, Generators, Artificial neural networks, Generative adversarial networks, brain atlas selection BibRef

Agrawal, P., Whitaker, R.T., Elhabian, S.Y.,
An Optimal, Generative Model for Estimating Multi-Label Probabilistic Maps,
MedImg(39), No. 7, July 2020, pp. 2316-2326.
IEEE DOI 2007
Probabilistic logic, Image segmentation, Shape, Brain modeling, Imaging, Sociology, Statistics, Probabilistic label maps, log ratio transformation BibRef

Ray, S.[Soumi], Kumar, V.[Vinod],
Information count and distribution matrix: A contemporary approach for content-based brain image indexing,
IJIST(30), No. 3, 2020, pp. 779-793.
DOI Link 2008
classification, feature extraction, image retrieval, indexing, pixel BibRef

Ji, J.Z.[Jun-Zhong], Xing, X.Y.[Xin-Ying], Yao, Y.[Yao], Li, J.W.[Jun-Wei], Zhang, X.D.[Xiao-Dan],
Convolutional kernels with an element-wise weighting mechanism for identifying abnormal brain connectivity patterns,
PR(109), 2021, pp. 107570.
Elsevier DOI 2009
Brain network classification, Convolutional kernels, Element-wise weighting mechanism, Topological features, Abnormal connectivity patterns BibRef

Han, M., Özdenizci, O., Wang, Y., Koike-Akino, T., Erdogmus, D.,
Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction,
SPLetters(27), 2020, pp. 1565-1569.
IEEE DOI 2009
Feature extraction, Task analysis, Decoding, Stress, Training, Physiology, Biomedical monitoring, Adversarial deep learning, stress assessment BibRef

Zhu, B., Sevick-Muraca, E.M., Nguyen, R.D., Shah, M.N.,
Cap-Based Transcranial Optical Tomography in an Awake Infant,
MedImg(39), No. 11, November 2020, pp. 3300-3308.
IEEE DOI 2011
Optical fiber couplers, Detectors, Optical imaging, Optical fiber devices, Functional magnetic resonance imaging, validation BibRef

Wang, L., Sun, B., Robinson, J., Jing, T., Fu, Y.,
EV-Action: Electromyography-Vision Multi-Modal Action Dataset,
FG20(160-167)
IEEE DOI 2102
biomechanics, electromyography, feature extraction, image motion analysis, image recognition, EMG BibRef

Saravanan, S., Karthigaivel, R.,
A fuzzy and spline based dynamic histogram equalization for contrast enhancement of brain images,
IJIST(31), No. 2, 2021, pp. 802-827.
DOI Link 2105
brightness, contrast enhancement, fuzzy and gray level, histogram equalization BibRef

Tang, Y.[Yunbo], Chen, D.[Dan], Li, X.L.[Xiao-Li],
Dimensionality Reduction Methods for Brain Imaging Data Analysis,
Surveys(54), No. 4, May 2021, pp. xx-yy.
DOI Link 2107
Survey, Brain Imaging. dimensionality reduction, factorization, feature learning, statistical tensor analysis, Brain imaging data, big data BibRef

Li, J.N.[Jian-Ning], Pimentel, P.[Pedro], Szengel, A.[Angelika], Ehlke, M.[Moritz], Lamecker, H.[Hans], Zachow, S.[Stefan], Estacio, L.[Laura], Doenitz, C.[Christian], Ramm, H.[Heiko], Shi, H.C.[Hao-Chen], Chen, X.J.[Xiao-Jun], Matzkin, F.[Franco], Newcombe, V.[Virginia], Ferrante, E.[Enzo], Jin, Y.[Yuan], Ellis, D.G.[David G.], Aizenberg, M.R.[Michele R.], Kodym, O.[Oldrich], Španel, M.[Michal], Herout, A.[Adam], Mainprize, J.G.[James G.], Fishman, Z.[Zachary], Hardisty, M.R.[Michael R.], Bayat, A.[Amirhossein], Shit, S.[Suprosanna], Wang, B.M.[Bo-Min], Liu, Z.[Zhi], Eder, M.[Matthias], Pepe, A.[Antonio], Gsaxner, C.[Christina], Alves, V.[Victor], Zefferer, U.[Ulrike], von Campe, G.[Gord], Pistracher, K.[Karin], Schäfer, U.[Ute], Schmalstieg, D.[Dieter], Menze, B.H.[Bjoern H.], Glocker, B.[Ben], Egger, J.[Jan],
AutoImplant 2020-First MICCAI Challenge on Automatic Cranial Implant Design,
MedImg(40), No. 9, September 2021, pp. 2329-2342.
IEEE DOI 2109
Skull, Shape, Implants, Cranial, Image reconstruction, Biomedical imaging, cranioplasty BibRef

Bai, P.L.[Pei-Liang], Safikhani, A.[Abolfazl], Michailidis, G.[George],
A Fast Detection Method of Break Points in Effective Connectivity Networks,
MedImg(41), No. 5, May 2022, pp. 1017-1030.
IEEE DOI 2205
Reactive power, Covariance matrices, Brain modeling, Hidden Markov models, Data models, Time series analysis, tuning parameters BibRef

Jiang, R.T.[Rong-Tao], Woo, C.W.[Choong-Wan], Qi, S.[Shile], Wu, J.[Jing], Sui, J.[Jing],
Interpreting Brain Biomarkers: Challenges and solutions in interpreting machine learning-based predictive neuroimaging,
SPMag(39), No. 4, July 2022, pp. 107-118.
IEEE DOI 2207
Neuroimaging, Precision medicine, Predictive models, Biomarkers, Brain modeling, Data models, Behavioral sciences BibRef

Wilms, M.[Matthias], Bannister, J.J.[Jordan J.], Mouches, P.[Pauline], MacDonald, M.E.[M. Ethan], Rajashekar, D.[Deepthi], Langner, S.[Sönke], Forkert, N.D.[Nils D.],
Invertible Modeling of Bidirectional Relationships in Neuroimaging With Normalizing Flows: Application to Brain Aging,
MedImg(41), No. 9, September 2022, pp. 2331-2347.
IEEE DOI 2209
Brain modeling, Morphology, Aging, Data models, Solid modeling, Predictive models, Bidirectional modeling, normalizing flows, brain aging BibRef

Yang, D.[Defu], Chen, J.Z.[Jia-Zhou], Yan, C.G.[Cheng-Gang], Kim, M.[Minjeong], Laurienti, P.J.[Paul J.], Styner, M.[Martin], Wu, G.R.[Guo-Rong],
Group-Wise Hub Identification by Learning Common Graph Embeddings on Grassmannian Manifold,
PAMI(44), No. 11, November 2022, pp. 8249-8260.
IEEE DOI 2210
Connectors, Manifolds, Neuroscience, Sociology, Diseases, Replicability, Psychiatry, Graph embedding, optimization, connector hub BibRef

Ha, S.[Seungbo], Lyu, I.[Ilwoo],
SPHARM-Net: Spherical Harmonics-Based Convolution for Cortical Parcellation,
MedImg(41), No. 10, October 2022, pp. 2739-2751.
IEEE DOI 2210
Convolution, Harmonic analysis, Surface morphology, Transforms, Task analysis, Semantics, Feature extraction, spherical harmonics BibRef

Zhang, J.J.[Jian-Jia], Zhou, L.P.[Lu-Ping], Wang, L.[Lei], Liu, M.T.[Meng-Ting], Shen, D.G.[Ding-Gang],
Diffusion Kernel Attention Network for Brain Disorder Classification,
MedImg(41), No. 10, October 2022, pp. 2814-2827.
IEEE DOI 2210
Transformers, Kernel, Feature extraction, Brain modeling, Task analysis, Time series analysis, Training, Attention network, transformer BibRef

Wu, E.Q.[Edmond Q.], Tang, Z.[Zhiri], Yao, Y.X.[Yu-Xuan], Qiu, X.Y.[Xu-Yi], Deng, P.Y.[Ping-Yu], Xiong, P.W.[Peng-Wen], Song, A.[Aiguo], Zhu, L.M.[Li-Min], Zhou, M.C.[Meng-Chu],
Scalable Gamma-Driven Multilayer Network for Brain Workload Detection Through Functional Near-Infrared Spectroscopy,
Cyber(52), No. 11, November 2022, pp. 12464-12478.
IEEE DOI 2211
Fatigue, Matrix decomposition, Nonhomogeneous media, Neurons, Brain modeling, Gamma distribution, Blood, Brain workload, Wigner-Ville distribution BibRef

Zhu, Q.[Qi], Xu, R.T.[Ru-Ting], Wang, R.[Ran], Xu, X.J.[Xi-Jia], Zhang, Z.Q.[Zhi-Qiang], Zhang, D.Q.[Dao-Qiang],
Stacked Topological Preserving Dynamic Brain Networks Representation and Classification,
MedImg(41), No. 11, November 2022, pp. 3473-3484.
IEEE DOI 2211
Time-domain analysis, Feature extraction, Diseases, Epilepsy, Correlation, Tensors, Sparse matrices, Dynamic brain networks, computer-aided diagnosis BibRef

Ma, K.[Kai], Wen, X.[Xuyun], Zhu, Q.[Qi], Zhang, D.Q.[Dao-Qiang],
Ordinal Pattern Tree: A New Representation Method for Brain Network Analysis,
MedImg(43), No. 4, April 2024, pp. 1526-1538.
IEEE DOI 2404
Kernel, Optimized production technology, Diseases, Graph theory, Feature extraction, Task analysis, Medical diagnosis, classification BibRef

Zhu, Q.[Qi], Li, S.R.[Sheng-Rong], Meng, X.S.[Xiang-Shui], Xu, Q.[Qiang], Zhang, Z.Q.[Zhi-Qiang], Shao, W.[Wei], Zhang, D.Q.[Dao-Qiang],
Spatio-Temporal Graph Hubness Propagation Model for Dynamic Brain Network Classification,
MedImg(43), No. 6, June 2024, pp. 2381-2394.
IEEE DOI 2406
Feature extraction, Network topology, Topology, Brain modeling, Functional magnetic resonance imaging, Medical diagnosis, brain disease diagnosis BibRef

Sun, L.[Liang], Fu, Y.L.[Yan-Ling], Zhao, J.Y.[Jun-Yong], Shao, W.[Wei], Zhu, Q.[Qi], Zhang, D.Q.[Dao-Qiang],
MAS-CL: An End-to-End Multi-Atlas Supervised Contrastive Learning Framework for Brain ROI Segmentation,
IP(33), 2024, pp. 4319-4333.
IEEE DOI 2408
Image segmentation, Contrastive learning, Task analysis, Labeling, Deep learning, Data augmentation, Brain modeling, brain segmentation BibRef

Wang, Y.J.[Yan-Jiang], Ma, J.C.[Ji-Chao], Chen, X.[Xue], Liu, B.[Baodi],
Accurately Modeling the Resting Brain Functional Correlations Using Wave Equation With Spatiotemporal Varying Hypergraph Laplacian,
MedImg(41), No. 12, December 2022, pp. 3787-3798.
IEEE DOI 2212
Brain modeling, Laplace equations, Correlation, Mathematical models, Propagation, Predictive models, resonance BibRef

Cui, H.[Hejie], Dai, W.[Wei], Zhu, Y.Q.[Yan-Qiao], Kan, X.[Xuan], Gu, A.A.C.[Antonio Aodong Chen], Lukemire, J.[Joshua], Zhan, L.[Liang], He, L.F.[Li-Fang], Guo, Y.[Ying], Yang, C.[Carl],
BrainGB: A Benchmark for Brain Network Analysis With Graph Neural Networks,
MedImg(42), No. 2, February 2023, pp. 493-506.
IEEE DOI 2302
Brain modeling, Network analyzers, Neuroimaging, Benchmark testing, Functional magnetic resonance imaging, Pipelines, Neuroscience, benchmarks BibRef

Song, X.[Xiao], Zhang, X.D.[Xiao-Dan], Ji, J.Z.[Jun-Zhong], Liu, Y.[Ying],
Multi-scale Superpixel based Hierarchical Attention model for brain CT classification,
JVCIR(91), 2023, pp. 103773.
Elsevier DOI 2303
Brian CT classification, Medical image processing, Multi-scale superpixel, Hierarchical attention BibRef

Gong, W.K.[Wei-Kang], Bai, S.[Song], Zheng, Y.Q.[Ying-Qiu], Smith, S.M.[Stephen M.], Beckmann, C.F.[Christian F.],
Supervised Phenotype Discovery From Multimodal Brain Imaging,
MedImg(42), No. 3, March 2023, pp. 834-849.
IEEE DOI 2303
Imaging, Task analysis, Magnetic resonance imaging, Predictive models, Multitasking, Loading, non-imaging derived phenotypes BibRef

Zou, Y.X.[Yong-Xiang], Cheng, L.[Long], Han, L.J.[Li-Jun], Li, Z.W.[Zheng-Wei], Song, L.P.[Lu-Ping],
Decoding Electromyographic Signal With Multiple Labels for Hand Gesture Recognition,
SPLetters(30), 2023, pp. 483-487.
IEEE DOI 2305
Feature extraction, Gesture recognition, Decoding, Aggregates, Muscles, Hospitals, Graph neural networks, Electromyogram decoding, multiple labels BibRef

Anand, D.V.[D. Vijay], Chung, M.K.[Moo K.],
Hodge Laplacian of Brain Networks,
MedImg(42), No. 5, May 2023, pp. 1563-1573.
IEEE DOI
WWW Link. 2305
Laplace equations, Brain modeling, Neuroimaging, Faces, Kernel, Inference algorithms, Graph theory, Hodge Laplacian, heat kernel smoothing BibRef

Guo, W.Y.[Wei-Yu], Jiang, N.[Ning], Farina, D.[Dario], Su, J.Y.[Jing-Yong], Wang, Z.[Zheng], Lin, C.[Chuang], Xiong, H.[Hui],
Multi-Attention Feature Fusion Network for Accurate Estimation of Finger Kinematics From Surface Electromyographic Signals,
HMS(53), No. 3, June 2023, pp. 512-519.
IEEE DOI 2306
Convolution, Smoothing methods, Long short term memory, Logic gates, Feature extraction, Kinematics, Estimation, surface EMG BibRef

Gürler, Z.[Zeynep], Rekik, I.[Islem],
Federated Brain Graph Evolution Prediction Using Decentralized Connectivity Datasets With Temporally-Varying Acquisitions,
MedImg(42), No. 7, July 2023, pp. 2022-2031.
IEEE DOI 2307
Hospitals, Trajectory, Brain modeling, Predictive models, Training, Training data, Task analysis, Federated GNN learning, data with missing timepoints BibRef

Vienneau, E.P.[Emelina P.], Byram, B.C.[Brett C.],
A Coded Excitation Framework for High SNR Transcranial Ultrasound Imaging,
MedImg(42), No. 10, October 2023, pp. 2886-2898.
IEEE DOI 2310
BibRef

Liu, J.W.[Jia-Wei], Xing, F.[Fuyong], Shaikh, A.[Abbas], French, B.[Brooke], Linguraru, M.G.[Marius George], Porras, A.R.[Antonio R],
Joint Cranial Bone Labeling and Landmark Detection in Pediatric CT Images Using Context Encoding,
MedImg(42), No. 10, October 2023, pp. 3117-3126.
IEEE DOI 2310
BibRef

Vindas, Y.[Yamil], Roux, E.[Emmanuel], Guépié, B.K.[Blaise Kévin], Almar, M.[Marilys], Delachartre, P.[Philippe],
Guided deep embedded clustering regularization for multifeature medical signal classification,
PR(143), 2023, pp. 109812.
Elsevier DOI 2310
Multifeature learning, Deep regularization, Guided training, Signal classification, Transcranial doppler BibRef

Wang, S.B.[Shao-Bo], Chen, Z.[Zaoqin], Liu, Y.Y.[Yang-Yang], Liu, Y.B.[Yu-Bing], Qian, Z.[Zhiyu], Meng, L.[Lin],
Relationship between reduced scattering coefficient and intracranial pressure in clinical patients under different brain edema states,
IJIST(33), No. 6, 2023, pp. 2194-2202.
DOI Link 2311
brain edema, intracranial pressure, near infrared technology, reduced scattering coefficient BibRef

Wang, Z.F.[Ze-Feng], Yao, J.F.[Jun-Feng], Xu, M.[Meiyan], Jiang, M.[Min], Su, J.S.[Jin-Song],
Transformer-based network with temporal depthwise convolutions for sEMG recognition,
PR(145), 2024, pp. 109967.
Elsevier DOI 2311
Surface electromyography, Feature learning, Gesture recognition, Transformer, Self-attention, Temporal depthwise convolution BibRef

Liu, J.Y.[Jing-Yu], Cui, W.G.[Wei-Gang], Chen, Y.P.[Yi-Peng], Ma, Y.L.[Yu-Lan], Dong, Q.[Qunxi], Cai, R.[Ran], Li, Y.[Yang], Hu, B.[Bin],
Deep Fusion of Multi-Template Using Spatio-Temporal Weighted Multi-Hypergraph Convolutional Networks for Brain Disease Analysis,
MedImg(43), No. 2, February 2024, pp. 860-873.
IEEE DOI 2402
Diseases, Time series analysis, Neurological diseases, Fuses, Correlation, Brain modeling, multi-template BibRef

Du, L.[Lei], Zhao, Y.[Ying], Zhang, J.T.[Jian-Ting], Shang, M.[Muheng], Zhang, J.[Jin], Han, J.W.[Jun-Wei],
Identification of Genetic Risk Factors Based on Disease Progression Derived From Longitudinal Brain Imaging Phenotypes,
MedImg(43), No. 3, March 2024, pp. 928-939.
IEEE DOI 2403
Genetics, Diseases, Imaging, Brain modeling, Neuroimaging, Trajectory, Data models, Brain imaging genetics, disease progression, sparse multi-task mixed-effects model BibRef

Liang, Q.M.[Quan-Min], Ma, J.J.[Jun-Ji], Chen, X.T.[Xi-Tian], Lin, Q.X.[Qi-Xiang], Shu, N.[Ni], Dai, Z.J.[Zheng-Jia], Lin, Y.[Ying],
A Hybrid Routing Pattern in Human Brain Structural Network Revealed By Evolutionary Computation,
MedImg(43), No. 5, May 2024, pp. 1895-1909.
IEEE DOI 2405
Routing, Head, Brain modeling, Navigation, Magnetic heads, Knowledge engineering, Image segmentation, Brain connectome, evolutionary computation BibRef

Liu, M.J.[Meng-Jun], Zhang, H.F.[Hui-Feng], Liu, M.X.[Mian-Xin], Chen, D.D.[Dong-Dong], Zhuang, Z.X.[Zi-Xu], Wang, X.[Xin], Zhang, L.C.[Li-Chi], Peng, D.H.[Dai-Hui], Wang, Q.[Qian],
Randomizing Human Brain Function Representation for Brain Disease Diagnosis,
MedImg(43), No. 7, July 2024, pp. 2537-2546.
IEEE DOI Code:
WWW Link. 2407
Brain, Diseases, Medical diagnosis, Functional magnetic resonance imaging, Transformers, brain disease diagnosis BibRef

Costa, L.[Lilia], Anacleto, O.[Osvaldo], Nascimento, D.C.[Diego C.], Smith, J.Q.[James Q.], Queen, C.M.[Catriona M.], Louzada, F.[Francisco], Nichols, T.[Thomas],
Evaluating brain group structure methods using hierarchical dynamic models,
PR(155), 2024, pp. 110687.
Elsevier DOI 2408
Multiregression dynamic model, Bayesian network, Group analysis, Cluster analysis, Hierarchical models BibRef

Kwarciak, K.[Kamil], Wodzinski, M.[Marek],
Deep Generative Networks for Heterogeneous Augmentation of Cranial Defects,
LIMIT23(1058-1066)
IEEE DOI 2401
BibRef

De, A.[Arijit], Tiwari, M.[Mona], Chowdhury, A.S.[Ananda S.],
3D Hippocampus Segmentation Using a Hog Based Loss Function with Majority Pooling,
ICIP23(2260-2264)
IEEE DOI 2312
BibRef

Zhdanov, M.[Maksim], Steinmann, S.[Saskia], Hoffmann, N.[Nico],
Investigating Brain Connectivity with Graph Neural Networks and GNNExplainer,
ICPR22(5155-5161)
IEEE DOI 2212
Deep learning, Pathology, Neuroscience, Mental disorders, Electroencephalography, Graph neural networks, Recording BibRef

Bohi, A.[Amine], Auzias, G.[Guillaume], Noûs, C.[Camille], Lefèvre, J.[Julien],
Comparing Vector Fields Across Surfaces: Interest for Characterizing the Orientations of Cortical Folds,
ICIP22(391-395)
IEEE DOI 2211
Geometry, Neuroimaging, Surface reconstruction, Task analysis, Surface treatment, Kidney, Image reconstruction, Vector field, Differential geometry BibRef

Huang, Y.W.[Ya-Wen], Zheng, F.[Feng], Sun, X.[Xu], Li, Y.X.[Yue-Xiang], Shao, L.[Ling], Zheng, Y.F.[Ye-Feng],
Generalized Brain Image Synthesis with Transferable Convolutional Sparse Coding Networks,
ECCV22(XXXIV:183-199).
Springer DOI 2211
BibRef

Zhang, K.[Ke], Wu, F.[Fei], Sun, J.X.[Jun-Xiao], Yang, G.Y.[Guan-Yu], Shu, H.Z.[Hua-Zhong], Kong, Y.Y.[You-Yong],
Iterative Seeded Region Growing for Brain Tissue Segmentation,
ICIP22(886-890)
IEEE DOI 2211
Training, Deep learning, Image segmentation, Brain, Magnetic resonance imaging, Iterative methods, Task analysis, supervoxel matching BibRef

Ranem, A.[Amin], González, C.[Camila], Mukhopadhyay, A.[Anirban],
Continual Hippocampus Segmentation with Transformers,
CLVision22(3710-3719)
IEEE DOI 2210
Image segmentation, Semantics, Sociology, Computer architecture, Artificial neural networks, Transformers, Task analysis BibRef

Zhang, M.[Min], Guo, Y.[Yang], Lei, N.[Na], Zhao, Z.[Zhou], Wu, J.F.[Jian-Feng], Xu, X.Y.[Xiao-Yin], Wang, Y.L.[Ya-Lin], Gu, X.F.[Xian-Feng],
Cortical Surface Shape Analysis Based on Alexandrov Polyhedra,
ICCV21(14224-14232)
IEEE DOI 2203
Geometry, Visualization, Shape, Prognostics and health management, Alzheimer's disease, Diseases, Biometrics, Segmentation, grouping and shape BibRef

Zhou, H.[Haiyu], Zhang, D.Q.[Dao-Qiang],
Graph-In-Graph Convolutional Networks for Brain Disease Diagnosis,
ICIP21(111-115)
IEEE DOI 2201
Correlation, Convolution, Image processing, Sociology, Data structures, Medical diagnosis, Graph convolutional network, brain disease diagnosis BibRef

Cheng, K.[Kellen], Atchaneeyasakul, K.[Kunakorn], Barakat, Z.[Zeid], Liebeskind, D.S.[David S.], Scalzo, F.[Fabien],
CT Perfusion Imaging of the Brain with Machine Learning,
ISVC21(II:41-52).
Springer DOI 2112
BibRef

Torbati, M.E.[Mahbaneh Eshaghzadeh], Tudorascu, D.L.[Dana L.], Minhas, D.S.[Davneet S.], Maillard, P.[Pauline], DeCarli, C.S.[Charles S.], Hwang, S.J.[Seong Jae],
Multi-scanner Harmonization of Paired Neuroimaging Data via Structure Preserving Embedding Learning,
CVAMD21(3277-3286)
IEEE DOI 2112
Neuroimaging, Measurement, Brain BibRef

Nguyen, N.P.[Nguyen P.], Yoo, Y.[Youngjin], Chekkoury, A.[Andrei], Eibenberger, E.[Eva], Re, T.J.[Thomas J.], Das, J.[Jyotipriya], Balachandran, A.[Abishek], Lui, Y.W.[Yvonne W.], Sanelli, P.C.[Pina C.], Schroeppel, T.J.[Thomas J.], Bodanapally, U.[Uttam], Nicolaou, S.[Savvas], White, T.A.[Tommi A.], Bunyak, F.[Filiz], Comaniciu, D.[Dorin], Gibson, E.[Eli],
Brain midline shift detection and quantification by a cascaded deep network pipeline on non-contrast computed tomography scans,
MIA-COVID19D21(487-495)
IEEE DOI 2112
Location awareness, Heating systems, Head, Computed tomography, Pipelines, Radiology BibRef

Cruz, R.S.[Rodrigo Santa], Lebrat, L.[Leo], Bourgeat, P.[Pierrick], Fookes, C.[Clinton], Fripp, J.[Jurgen], Salvado, O.[Olivier],
DeepCSR: A 3D Deep Learning Approach for Cortical Surface Reconstruction,
WACV21(806-815)
IEEE DOI 2106
Deep learning, Surface reconstruction, Image resolution, Feature extraction BibRef

Gribel, D.[Daniel], Vidal, T.[Thibaut], Gendreau, M.[Michel],
Assortative-Constrained Stochastic Block Models,
ICPR21(6212-6218)
IEEE DOI 2105
networks for cerebral-cortex activity regions. Maximum likelihood detection, Cats, Image edge detection, Stochastic processes, Brain modeling, Partitioning algorithms BibRef

Murabito, F., Palazzo, S., Salanitri, F.P.[F. Proietto], Rundo, F., Bagci, U., Giordano, D., Leonardi, R., Spampinato, C.,
Deep Recurrent-Convolutional Model for Automated Segmentation of Craniomaxillofacial CT Scans,
ICPR21(9062-9067)
IEEE DOI 2105
Convolutional codes, Image segmentation, Shape, Computed tomography, Atmospheric modeling, Semantics, Imaging, Pharyngeal airways BibRef

Barile, B.[Beradino], Marzullo, A.[Aldo], Stamile, C.[Claudio], Durand-Dubief, F.[Francoise], Sappey-Marinier, D.[Dominique],
Tensor Factorization of Brain Structural Graph for Unsupervised Classification in Multiple Sclerosis,
ICPR21(5052-5059)
IEEE DOI 2105
Tensors, Multiple sclerosis, Pathological processes, Brain modeling, Data models, Classification algorithms, Pattern recognition BibRef

Rojas, A.[Andrés], Kroupi, E.[Eleni], Martens, G.[Géraldine], Thibaut, A.[Aurore], Barra, A.[Alice], Laureys, S.[Steven], Ruffini, G.[Giulio], Soria-Frisch, A.[Aureli],
Prediction of Minimally Conscious State Responder Patients to Non-invasive Brain Stimulation Using Machine Learning Algorithms,
AIHA20(515-525).
Springer DOI 2103
Transcranial Electrical Stimulation (tES) therapy. BibRef

Rahali, R., Ben Salem, Y., Dridi, N., Dahman, H.,
B-Spline Level Set For Drosophila Image Segmentation,
ICIP20(413-417)
IEEE DOI 2011
Level set, Image segmentation, Splines (mathematics), Biology, Noise measurement, Clustering algorithms, Smoothing methods, DICE BibRef

Wen, C.F.[Cheng-Feng], Lei, N.[Na], Ma, M.[Ming], Qi, X.[Xin], Zhang, W.[Wen], Wang, Y.L.[Ya-Lin], Gu, X.F.[Xian-Feng],
Surface Foliation Based Brain Morphometry Analysis,
MFCA19(186-195).
Springer DOI 1912
BibRef

Tward, D.[Daniel], Li, X.[Xu], Huo, B.X.[Bing-Xing], Lee, B.[Brian], Mitra, P.[Partha], Miller, M.[Michael],
3d Mapping of Serial Histology Sections with Anomalies Using a Novel Robust Deformable Registration Algorithm,
MFCA19(162-173).
Springer DOI 1912
BibRef

Marinescu, R.V.[Razvan V.], Eshaghi, A.[Arman], Alexander, D.C.[Daniel C.], Golland, P.[Polina],
Brainpainter: A Software for the Visualisation of Brain Structures, Biomarkers and Associated Pathological Processes,
MBIA19(112-120).
Springer DOI 1912
BibRef

Sagindykov, T.B., Brazhe, A.R., Sorokin, D.V.,
Preprocessing and Registration of Miniscope-based Calcium Imaging Of The Rodent Brain,
PTVSBB19(185-188).
DOI Link 1912
BibRef

Rashed, E.A., Gomez-Tames, J., Hirata, A.,
Generation of Head Models for Brain Stimulation Using Deep Convolution Networks,
ICIP19(2621-2625)
IEEE DOI 1910
Transcranial magnetic stimulation, image segmentation, deep learning, convolution neural networks BibRef

Yang, C., Lo, C., Wang, H., Chou, J., FrankWang, Y.,
Weakly-Supervised Learning for Attention-Guided Skull Fracture Classification In Computed Tomography Imaging,
ICIP19(1337-1341)
IEEE DOI 1910
Medical imaging, image attention, weakly-supervised learning, deep learning, convolutional neural networks BibRef

Sarbazvatan, S., Ventura, R., Esteves, F.F., Lima, S.Q., Sanches, J.M.,
A Novel Graph-Based Approach for Seriation of Mouse Brain Cross-Section from Images,
IbPRIA19(I:461-471).
Springer DOI 1910
BibRef

Mohanty, K.[Kaustav], Yousefian, O.[Omid], Karbalaeisadegh, Y.[Yasamin], Ulrich, M.[Micah], Muller, M.[Marie],
Predicting Structural Properties of Cortical Bone by Combining Ultrasonic Attenuation and an Artificial Neural Network (ANN): 2-D FDTD Study,
ICIAR19(I:407-417).
Springer DOI 1909
BibRef

Fonal, K., Zdunek, R., Wolczowski, A.,
Feature-Fusion HALS-based Algorithm for Linked CP Decomposition Model in Application to Joint EMG/MMG Signal Classification,
ICPR18(928-933)
IEEE DOI 1812
Tensile stress, Feature extraction, Electromyography, Brain modeling, Pattern recognition, Numerical models, EMG/MMG signal classification BibRef

Guo, Y.L.[Yi-Luan], Nejati, H.[Hossein], Cheung, N.M.[Ngai-Man],
Deep neural networks on graph signals for brain imaging analysis,
ICIP17(3295-3299)
IEEE DOI 1803
Biological neural networks, Brain modeling, Convolution, Feature extraction, Imaging, Sensors, Brain imaging, autoencoder, graph signal processing BibRef

Robles, F.A.B.[Felipe-Andrés Bello], Panerai, R.B.[Ronney B.], Pacheco, M.C.[Max Chacón],
Linear Modelling of Cerebral Autoregulation System Using Genetic Algorithms,
CIARP17(94-101).
Springer DOI 1802
BibRef

Xie, S.D.[Shu-Dong], Leow, W.K.[Wee Kheng], Lim, T.C.[Thiam Chye],
Laplacian Deformation with Symmetry Constraints for Reconstruction of Defective Skulls,
CAIP17(II: 24-35).
Springer DOI 1708
BibRef

Ghaemmaghami, P., Nabi, M., Yan, Y., Sebe, N.,
Sparse-coded cross-domain adaptation from the visual to the brain domain,
ICPR16(4214-4219)
IEEE DOI 1705
Adaptation models, Brain, Decoding, Dictionaries, Machine learning algorithms, Neuroimaging, Visualization BibRef

Gordon, J., Lerner, B.,
Exposing and modeling underlying mechanisms in ALS with machine learning,
ICPR16(2168-2173)
IEEE DOI 1705
Clinical trials, Databases, Diseases, Prediction algorithms, Predictive models, Radio frequency, Vegetation BibRef

Turgut, U.O.[Umut Orcun], Gokcay, D.[Didem],
Shape Preservation Based on Gaussian Radial Basis Function Interpolation on Human Corpus Callosum,
SeSAME16(118-132).
Springer DOI 1703
BibRef

Liu, Y., Zhang, M., Yang, W., Lu, Z., Feng, Q.,
Hippocampus Segmentation Based on Orientation-Scale Descriptor and Sparse Coding,
DICTA16(1-8)
IEEE DOI 1701
Deformable models BibRef

Robinson, E.C., Glocker, B., Rajchl, M., Rueckert, D.,
Discrete Optimisation for Group-Wise Cortical Surface Atlasing,
WBIR16(442-448)
IEEE DOI 1612
BibRef

Hafri, M., Jennane, R., Lespessailles, E., Toumi, H.,
Dual active contours model for HR-pQCT cortical bone segmentation,
ICPR16(2270-2275)
IEEE DOI 1705
Active contours, Bones, Computed tomography, Cortical bone, Image segmentation, Nonhomogeneous media, HR-pQCT, Segmentation, active contours, cortical bone, local, energy BibRef