21.9.2 Brain, Cortex, Dementia

Chapter Contents (Back)
Brain. Cortex. Dementia. Includes other mental problems, especially MCI: Mild cognitive impairment.
See also Brain, Cortex, Alzheimer's Disease.
See also Brain, Cortex, Registration, Alignment, MRI, Other.
See also Functional Magnetic Resonance, fMRI.

Studholme, C., Cardenas, V., Song, E., Ezekiel, F., Maudsley, A.A., Weiner, M.,
Accurate Template-Based Correction of Brain MRI Intensity Distortion With Application to Dementia and Aging,
MedImg(23), No. 1, January 2004, pp. 99-110.
IEEE Abstract. 0403
BibRef

Zhao, M.B.[Ming-Bo], Chan, R.H.M., Tang, P.[Peng], Chow, T.W.S., Wong, S.W.H.,
Trace Ratio Linear Discriminant Analysis for Medical Diagnosis: A Case Study of Dementia,
SPLetters(20), No. 5, May 2013, pp. 431-434.
IEEE DOI 1304
BibRef

He, M., Baker, S.L., Shah, V.D., Lockhart, S.N., Jagust, W.J.,
Scan-Time Corrections for 80-100-min Standardizetd Uptake Volume Ratios to Measure the 18F-AV-1451 Tracer for Tau Imaging,
MedImg(38), No. 3, March 2019, pp. 697-709.
IEEE DOI 1903
Dementia, Image reconstruction, Interpolation, Training, Magnetic resonance imaging, Tau, PET Imaging, SUVR, scan-time error, Alzheimer's disease BibRef

Jie, B.[Biao], Liu, M.X.[Ming-Xia], Zhang, D.Q.[Dao-Qiang], Shen, D.G.[Ding-Gang],
Sub-Network Kernels for Measuring Similarity of Brain Connectivity Networks in Disease Diagnosis,
IP(27), No. 5, May 2018, pp. 2340-2353.
IEEE DOI 1804
biomedical MRI, brain, cognition, diseases, graph theory, image classification, medical image processing, neurophysiology, mild cognitive impairment (MCI) BibRef

Li, Y., Yang, H., Lei, B., Liu, J., Wee, C.,
Novel Effective Connectivity Inference Using Ultra-Group Constrained Orthogonal Forward Regression and Elastic Multilayer Perceptron Classifier for MCI Identification,
MedImg(38), No. 5, May 2019, pp. 1227-1239.
IEEE DOI 1905
Feature extraction, Time series analysis, Functional magnetic resonance imaging, Diseases, machine learning BibRef

Huang, W., Luo, M., Liu, X., Zhang, P., Ding, H., Xue, W., Ni, D.,
Arterial Spin Labeling Images Synthesis From sMRI Using Unbalanced Deep Discriminant Learning,
MedImg(38), No. 10, October 2019, pp. 2338-2351.
IEEE DOI 1910
Deep learning, Dementia, Biomedical imaging, Medical diagnosis, Magnetic resonance imaging, Magnetic resonance imaging (MRI), machine learning BibRef

Bharanidharan, N., Rajaguru, H.[Harikumar],
Performance enhancement of swarm intelligence techniques in dementia classification using dragonfly-based hybrid algorithms,
IJIST(30), No. 1, 2020, pp. 57-74.
DOI Link 2002
DA-PSO, dementia, hybrid swarm intelligence, MRI, OASIS BibRef

Bharanidharan, N., Rajaguru, H.[Harikumar],
Improved chicken swarm optimization to classify dementia MRI images using a novel controlled randomness optimization algorithm,
IJIST(30), No. 3, 2020, pp. 605-620.
DOI Link 2008
CSO, dementia, ICSO, meta-heuristic, MRI BibRef

Du, L., Liu, F., Liu, K., Yao, X., Risacher, S.L., Han, J., Saykin, A.J., Shen, L.,
Associating Multi-Modal Brain Imaging Phenotypes and Genetic Risk Factors via a Dirty Multi-Task Learning Method,
MedImg(39), No. 11, November 2020, pp. 3416-3428.
IEEE DOI 2011
Imaging, Genetics, Task analysis, Brain, Neuroimaging, Dementia, Brain imaging genetics, sparse canonical correlation analysis, the dirty multi-task SCCA BibRef

Li, Y., Liu, J., Tang, Z., Lei, B.,
Deep Spatial-Temporal Feature Fusion From Adaptive Dynamic Functional Connectivity for MCI Identification,
MedImg(39), No. 9, September 2020, pp. 2818-2830.
IEEE DOI 2009
Time series analysis, Feature extraction, Diffusion tensor imaging, Adaptive systems, Topology, Diseases, spatial-temporal feature BibRef

Lella, E.[Eufemia], Vessio, G.[Gennaro],
Ensembling complex network 'perspectives' for mild cognitive impairment detection with artificial neural networks,
PRL(136), 2020, pp. 168-174.
Elsevier DOI 2008
Decision support systems, Mild cognitive impairment, Diffusion-weighted imaging, Complex networks, Artificial neural networks BibRef

Jiao, Z.Q.[Zhu-Qing], Jiao, T.X.[Ting-Xuan], Zhang, J.H.[Jia-Hao], Shi, H.F.[Hai-Feng], Wu, B.[Bona], Zhang, Y.D.[Yu-Dong],
Sparse structure deep network embedding for transforming brain functional network in early mild cognitive impairment classification,
IJIST(31), No. 3, 2021, pp. 1197-1210.
DOI Link 2108
brain functional network, dilated convolutional neural network (DCNN), transform BibRef

Yang, P., Zhou, F., Ni, D., Xu, Y., Chen, S., Wang, T., Lei, B.,
Fused Sparse Network Learning for Longitudinal Analysis of Mild Cognitive Impairment,
Cyber(51), No. 1, January 2021, pp. 233-246.
IEEE DOI 2012
Diseases, Databases, Time series analysis, Imaging, Monitoring, Brain modeling, Task analysis, Fused sparse network (FSN), similarity network fusion (SNF) BibRef

Bharanidharan, N., Rajaguru, H.[Harikumar],
Dementia MRI image classification using transformation technique based on elephant herding optimization with Randomized Adam method for updating the hyper-parameters,
IJIST(31), No. 3, 2021, pp. 1221-1245.
DOI Link 2108
dementia, elephant herding optimization, evolutionary algorithms, MRI, swarm intelligence BibRef

Perugia, G.[Giulia], Díaz-Boladeras, M.[Marta], Català-Mallofré, A.[Andreu], Barakova, E.I.[Emilia I.], Rauterberg, M.[Matthias],
ENGAGE-DEM: A Model of Engagement of People With Dementia,
AffCom(13), No. 2, April 2022, pp. 926-943.
IEEE DOI 2206
Dementia, Computational modeling, Mathematical model, Task analysis, Physiology, Games, Atmospheric measurements, social agents/robotics BibRef

Li, Y.[Yang], Liu, J.Y.[Jing-Yu], Jiang, Y.Q.[Yi-Qiao], Liu, Y.[Yu], Lei, B.Y.[Bai-Ying],
Virtual Adversarial Training-Based Deep Feature Aggregation Network From Dynamic Effective Connectivity for MCI Identification,
MedImg(41), No. 1, January 2022, pp. 237-251.
IEEE DOI 2201
Feature extraction, Diseases, Heuristic algorithms, Brain modeling, Time series analysis, Deep learning, Training, virtual adversarial training BibRef

da Silva, V.F.[Vernon Furtado], Silva, D.A.S.[Diego Augusto Santos], Martins, P.C.[Priscila Custódio], Calomeni, M.R.[Mauricio Rocha], de Aquino Freire, I.[Ivete], Militão, A.G.[Angeliete Garcês], Borges, C.J.[Célio José], de Barros-Vilela-Junior, G.[Guanis], de Moraes, M.A.[Mario Antônio], Silva, A.J.R.M.[Antônio José Rocha Martins], de Almeida-Marinho, D.[Daniel], Ribeiro, D.E.C.[Domingos Edno Castro], Ribeiro, E.C.[Edinilson Castro], Valentim-Silva, J.R.[João Rafael],
Effect of physical exercise and noninvasive brain stimulation on cognition and dementia of elderly people with frailty: A randomized study,
IJIST(32), No. 6, 2022, pp. 1941-1952.
DOI Link 2212
aging, brain stimulation, inhibitory control, qEEG, working memory BibRef

Kang, E.[Eunsong], Heo, D.W.[Da-Woon], Lee, J.[Jiwon], Suk, H.I.[Heung-II],
A Learnable Counter-Condition Analysis Framework for Functional Connectivity-Based Neurological Disorder Diagnosis,
MedImg(43), No. 4, April 2024, pp. 1377-1387.
IEEE DOI 2404
Diseases, Feature extraction, Brain modeling, Adaptation models, Analytical models, Support vector machines, Medical diagnosis, explainable AI BibRef


Tiwari, A.[Abhishek], Singhal, A.[Ananya], Shigwan, S.J.[Saurabh J.], Singh, R.K.[Rajeev Kumar],
Deep Learning Framework using Sparse Diffusion MRI for Diagnosis of Frontotemporal Dementia,
BioIm23(3823-3829)
IEEE DOI 2401
BibRef

Qiao, J.P.[Jian-Ping], Liu, H.J.[Hong-Jia], Wang, R.[Rong], Wang, Z.S.[Zhi-Shun], Sun, J.[Jiande],
The Multivariate Transformer Network for Mild Cognitive Impairment Identification,
ICIP23(1140-1144)
IEEE DOI 2312
BibRef

Amini, M.[Morteza], Mahmoodi, T.[Tayeb], Sajedi, H.[Hedieh], Mirzaea, S.[Sayeh],
Detection of Cortical Demantia in MRI Images Using Convolutional Autoencoder Neural Network,
IPRIA21(1-3)
IEEE DOI 2201
Image analysis, Magnetic resonance imaging, Brain mapping, Pattern recognition, Convolutional neural networks, Classification BibRef

Tang, H.T.[Hao-Teng], Guo, L.[Lei], Dennis, E.[Emily], Thompson, P.M.[Paul M.], Huang, H.[Heng], Ajilore, O.[Olusola], Leow, A.D.[Alex D.], Zhan, L.[Liang],
Classifying Stages of Mild Cognitive Impairment via Augmented Graph Embedding,
MBIA19(30-38).
Springer DOI 1912
BibRef

Chakraborty, R., Vemuri, B.C.,
Statistical analysis of longitudinal data and applications to neuro-imaging,
ICIP17(211-214)
IEEE DOI 1803
Dementia, Electronics packaging, Frequency modulation, Manifolds, Measurement, Statistical analysis, Trajectory, Trajectories BibRef

Ding, J.W.[Jun-Wei], Huang, Q.[Qiu],
Prediction of MCI to AD conversion using Laplace Eigenmaps learned from FDG and MRI images of AD patients and healthy controls,
ICIVC17(660-664)
IEEE DOI 1708
Diseases, Hippocampus, Image reconstruction, Magnetic resonance imaging, Prognostics and health management, Proteins, Support vector machines, alzheimers, image processing, manifold, medical image, prediction BibRef

Endo, T., Ukita, N., Tanaka, H., Hagita, N., Nakamura, S., Adachi, H., Ikeda, M., Kazui, H., Kudo, T.,
Initial response time measurement in eye movement for dementia screening test,
MVA17(262-265)
DOI Link 1708
Cameras, Dementia, Facial features, Feature extraction, Iris, Time, factors BibRef

Yang, X.[Xi], Jin, Y.[Yan], Chen, X.B.[Xiao-Bo], Zhang, H.[Han], Li, G.[Gang], Shen, D.G.[Ding-Gang],
Functional Connectivity Network Fusion with Dynamic Thresholding for MCI Diagnosis,
MLMI16(246-253).
Springer DOI 1611
BibRef

Li, F.[Feng], Tran, L.[Loc], Thung, K.H.[Kim-Han], Ji, S.W.[Shui-Wang], Shen, D.G.[Ding-Gang], Li, J.[Jiang],
Robust Deep Learning for Improved Classification of AD/MCI Patients,
MLMI14(240-247).
Springer DOI 1410
BibRef

Stühler, E.[Elisabeth], Berthold, M.R.[Michael R.],
Dementia-Related Features in Longitudinal MRI: Tracking Keypoints over Time,
MCV14(59-70).
Springer DOI 1501
BibRef

Díaz, G.[Gloria], García-Polo, P.[Pablo], Mato, V.[Virginia], Alfayate, E.[Eva], Hernández-Tamames, J.A.[Juan Antonio], Malpica, N.[Norberto],
Predicting Very Early Stage Mild Cognitive Impairment Based on a Voxel-wise Arterial Spin Labeling Analysis,
CIARP14(714-721).
Springer DOI 1411
BibRef

Hu, C.H.[Chen-Hui], Hua, X.[Xue], Thompson, P.M.[Paul M.], El Fakhri, G.[Georges], Li, Q.Z.[Quan-Zheng],
Inferring Sources of Dementia Progression with Network Diffusion Model,
MLMI14(42-49).
Springer DOI 1410
BibRef

Bron, E.[Esther], Smits, M.[Marion], van Swieten, J.[John], Niessen, W.[Wiro], Klein, S.[Stefan],
Feature Selection Based on SVM Significance Maps for Classification of Dementia,
MLMI14(272-279).
Springer DOI 1410
BibRef

Simoes, R.[Rita], Slump, C.[Cornelis], van Cappellen-van Walsum, A.M.[Anne-Marie],
Using local texture maps of brain MR images to detect Mild Cognitive Impairment,
ICPR12(153-156).
WWW Link. 1302
BibRef

Nir, T.M.[Talia M.], Jahanshad, N.[Neda], Toga, A.W.[Arthur W.], Jack, C.R.[Clifford R.], Weiner, M.W.[Michael W.], Thompson, P.M.[Paul M.],
Connectivity Network Breakdown Predicts Imminent Volumetric Atrophy in Early Mild Cognitive Impairment,
MBIA12(41-50).
Springer DOI 1210
BibRef

Gray, K.R.[Katherine R.], Aljabar, P.[Paul], Heckemann, R.A.[Rolf A.], Hammers, A.[Alexander], Rueckert, D.[Daniel],
Random Forest-Based Manifold Learning for Classification of Imaging Data in Dementia,
MLMI11(159-166).
Springer DOI 1109
BibRef

Tosun, D.[Duygu], Weiner, M.W.[Michael W.], Schuff, N.[Norbert], Rosen, H.[Howard], Miller, B.L.[Bruce L.],
Joint Independent Component Analysis of Brain Perfusion and Structural Magnetic Resonance Images in Dementia,
ICPR10(2720-2723).
IEEE DOI 1008
BibRef

Kondou, Y.[Youhei], Kawasumi, M.[Mikiko], Yamamoto, O.[Osami], Yamada, M.[Muneo], Yamamoto, S.[Shin], Nakanno, T.[Tomoaki],
Study of Early Screening Method of Dementia and Its Systemization,
MVA09(82-).
PDF File. 0905
BibRef

Akgul, C.B.[Ceyhun Burak], Ekin, A.[Ahmet],
A Probabilistic Information Fusion Approach to MR-based Automated Diagnosis of Dementia,
ICPR10(265-268).
IEEE DOI 1008
BibRef

Akgül, C.B.[Ceyhun Burak], Ünay, D.[Devrim], Ekin, A.[Ahmet],
Automated diagnosis of Alzheimer's disease using image similarity and user feedback,
CIVR09(Article No 34).
DOI Link 0907
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Brain, Cortex, Alzheimer's Disease .


Last update:Apr 18, 2024 at 11:38:49