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DOI Link
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clustering; MRI; aging; MCI; Alzheimer's disease
BibRef
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Martínez-Murcia, F.J.,
LVQ-SVM based CAD tool applied to structural MRI for the diagnosis of
the Alzheimer's disease,
PRL(34), No. 14, 2013, pp. 1725-1733.
Elsevier DOI
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Alzheimer's disease
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Initiative, T.A.D.N.[The Alzheimers Disease Neuroimaging],
The clique potential of Markov random field in a random experiment
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IJIST(23), No. 4, 2013, pp. 304-313.
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magnetic resonance imaging
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Initiative, T.A.D.N.[The Alzheimers Disease Neuroimaging],
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IJIST(24), No. 3, 2014, pp. 224-238.
DOI Link
1408
magnetic resonance imaging
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Yang, W.J.[Wen-Ji],
Huang, W.[Wei],
Chen, S.X.[Shan-Xue],
Partial Volume Correction on ASL-MRI and Its Application on Alzheimer's
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DOI Link
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BibRef
Earlier:
Computer Aided Diagnosis of Alzheimer's Disease from MRI Brain Images,
ICIAR12(II: 259-267).
Springer DOI
1206
Alzheimer's disease
BibRef
Seo, D.H.[Do-Hyung],
Ho, J.[Jeffrey],
Vemuri, B.C.[Baba C.],
Covariant Image Representation with Applications to Classification
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IJCV(116), No. 2, January 2016, pp. 190-209.
Springer DOI
1602
Apply to MR for Alzheimers and MR detection of seizures.
BibRef
Rabeh, A.B.[Amira Ben],
Benzarti, F.[Faouzi],
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Segmentation of brain MRI using active contour model,
IJIST(27), No. 1, 2017, pp. 3-11.
DOI Link
1704
Alzheimer disease
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Cao, P.[Peng],
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Zhao, D.[Dazhe],
Huang, M.[Min],
Zaiane, O.[Osmar],
Sparse shared structure based multi-task learning for MRI based
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PR(72), No. 1, 2017, pp. 219-235.
Elsevier DOI
1708
Alzheimer's, disease
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Cao, P.[Peng],
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L2,1-l1 regularized nonlinear multi-task representation learning
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Elsevier DOI
1804
Alzheimer's disease, Regression, Sparse learning,
Multi-task learning, Kernel method
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Zhang, Y.[Yu],
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Liu, M.X.[Ming-Xia],
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Shen, D.G.[Ding-Gang],
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PR(88), 2019, pp. 421-430.
Elsevier DOI
1901
Alzheimers disease, Mild cognitive impairment,
Resting-state functional magnetic resonance imaging (rs-fMRI),
Diagnosis
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Zhou, L.P.[Lu-Ping],
Wang, Y.P.[Ya-Ping],
Li, Y.[Yang],
Yap, P.T.[Pew-Thian],
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Adni,
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CVPR11(1073-1080).
IEEE DOI
1106
T1-weighted MRI for mild cognitive impairment.
BibRef
Yu, R.P.[Ren-Ping],
Qiao, L.S.[Li-Shan],
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Lee, S.W.[Seong-Whan],
Fei, X.[Xuan],
Shen, D.G.[Ding-Gang],
Weighted graph regularized sparse brain network construction for MCI
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PR(90), 2019, pp. 220-231.
Elsevier DOI
1903
Graph Laplacian regularization, Sparse representation,
Brain functional network, Mild cognitive impairment (MCI)
BibRef
Jie, B.[Biao],
Zhang, D.Q.[Dao-Qiang],
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Structural Feature Selection for Connectivity Network-Based MCI
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MBIA12(175-184).
Springer DOI
1210
BibRef
Kam, T.,
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Shen, D.G.,
Deep Learning of Static and Dynamic Brain Functional Networks for
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MedImg(39), No. 2, February 2020, pp. 478-487.
IEEE DOI
2002
Ions, Noise measurement, Diagnosis,
convolutional neural networks, brain network,
functional MRI
BibRef
Choi, J.Y.,
Lee, B.,
Combining of Multiple Deep Networks via Ensemble Generalization Loss,
Based on MRI Images, for Alzheimer's Disease Classification,
SPLetters(27), 2020, pp. 206-210.
IEEE DOI
2002
Alzheimer's disease classification, ensemble deep learning, generalization loss
BibRef
Lian, C.F.[Chun-Feng],
Liu, M.X.[Ming-Xia],
Zhang, J.[Jun],
Shen, D.G.[Ding-Gang],
Hierarchical Fully Convolutional Network for Joint Atrophy
Localization and Alzheimer's Disease Diagnosis Using Structural MRI,
PAMI(42), No. 4, April 2020, pp. 880-893.
IEEE DOI
2003
Feature extraction, Solid modeling, Atrophy, Brain modeling,
Alzheimer's disease, Medical diagnosis, Support vector machines,
structural MRI
BibRef
Zhang, J.[Jun],
Liu, M.X.[Ming-Xia],
An, L.[Le],
Gao, Y.Z.[Yao-Zong],
Shen, D.G.[Ding-Gang],
Landmark-Based Alzheimer's Disease Diagnosis Using Longitudinal
Structural MR Images,
MCV16(35-45).
Springer DOI
1711
BibRef
Zhang, Y.T.[Ying-Teng],
Liu, S.Q.[Shen-Quan],
Yu, X.L.[Xiao-Li],
Longitudinal structural MRI analysis and classification in
Alzheimer's disease and mild cognitive impairment,
IJIST(30), No. 2, 2020, pp. 421-433.
DOI Link
2005
Alzheimer's disease, gray matter volume, longitudinal analysis,
longitudinal classification, mild cognitive impairment
BibRef
Zhu, W.Y.[Wen-Yong],
Sun, L.[Liang],
Huang, J.S.[Jia-Shuang],
Han, L.X.[Liang-Xiu],
Zhang, D.Q.[Dao-Qiang],
Dual Attention Multi-Instance Deep Learning for Alzheimer's Disease
Diagnosis With Structural MRI,
MedImg(40), No. 9, September 2021, pp. 2354-2366.
IEEE DOI
2109
Feature extraction, Diseases, Pathology, Deep learning,
Medical diagnosis, Magnetic resonance imaging, Grey matter, sMRI
BibRef
Basheera, S.[Shaik],
Ram, M.S.S.[M Satya Sai],
Deep learning based Alzheimer's disease early diagnosis using T2w
segmented gray matter MRI,
IJIST(31), No. 3, 2021, pp. 1692-1710.
DOI Link
2108
Alzheimer's disease, classification, CNN, deep learning, gray matter
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Karim, R.[Razaul],
Shahrior, A.[Ashef],
Rahman, M.M.[Mohammad Motiur],
Machine learning-based tri-stage classification of Alzheimer's
progressive neurodegenerative disease using PCA and mRMR administered
textural, orientational, and spatial features,
IJIST(31), No. 4, 2021, pp. 2060-2074.
DOI Link
2112
Alzheimer's, feature extraction, machine learning, MRI, VLAD
BibRef
Eroglu, Y.[Yesim],
Yildirim, M.[Muhammed],
Cinar, A.[Ahmet],
mRMR-based hybrid convolutional neural network model for
classification of Alzheimer's disease on brain magnetic resonance
images,
IJIST(32), No. 2, 2022, pp. 517-527.
DOI Link
2203
Alzheimer's disease, classification, KNN, machine learning, MRI, SVM
BibRef
Babu, G.S.[G. Stalin],
Rao, S.N.T.[S. N. Tirumala],
Rao, R.R.[R. Rajeswara],
Automated assessment for Alzheimer's disease diagnosis from MRI
images: Meta-heuristic assisted deep learning model,
IJIST(32), No. 2, 2022, pp. 544-563.
DOI Link
2203
Alzheimer disease, CG-DU algorithm, DCNN, geometric Haralick,
gray wolf optimizer
BibRef
Yu, L.[Lu],
Xiang, W.[Wei],
Fang, J.[Juan],
Chen, Y.P.P.[Yi-Ping Phoebe],
Zhu, R.F.[Rui-Feng],
A novel explainable neural network for Alzheimer's disease diagnosis,
PR(131), 2022, pp. 108876.
Elsevier DOI
2208
Explainable neural networks, XAI, High-resolution heatmap, MRI
BibRef
Pei, Z.[Zhao],
Wan, Z.Y.[Zhi-Yang],
Zhang, Y.N.[Yan-Ning],
Wang, M.[Miao],
Leng, C.C.[Cheng-Cai],
Yang, Y.H.[Yee-Hong],
Multi-scale attention-based pseudo-3D convolution neural network for
Alzheimer's disease diagnosis using structural MRI,
PR(131), 2022, pp. 108825.
Elsevier DOI
2208
Diagnosis of Alzheimer's disease, Pseudo-3D,
Attention mechanism, Multi-scale, Joint loss function
BibRef
Cai, H.J.[Hong-Jie],
Gao, Y.[Yue],
Liu, M.H.[Man-Hua],
Graph Transformer Geometric Learning of Brain Networks Using
Multimodal MR Images for Brain Age Estimation,
MedImg(42), No. 2, February 2023, pp. 456-466.
IEEE DOI
2302
Estimation, Diffusion tensor imaging, Transformers, Aging,
Brain modeling, Data models, Convolutional neural networks,
Alzheimer's disease
BibRef
Jung, E.[Euijin],
Luna, M.[Miguel],
Park, S.H.[Sang Hyun],
Conditional GAN with 3D discriminator for MRI generation of
Alzheimer's disease progression,
PR(133), 2023, pp. 109061.
Elsevier DOI
2210
Conditional GAN, Alzheimer's disease, 3D Discriminator,
Magnetic resonance image generation, Adaptive identity loss
BibRef
Qasim Abbas, S.,
Chi, L.H.[Lian-Hua],
Chen, Y.P.P.[Yi-Ping Phoebe],
Transformed domain convolutional neural network for Alzheimer's
disease diagnosis using structural MRI,
PR(133), 2023, pp. 109031.
Elsevier DOI
2210
Alzheimer disease (AD) detection, Brain disease,
Convolutional neural network (CNN), Supervised learning,
AD diagnosis
BibRef
Ouyang, J.H.[Jia-Hong],
Zhao, Q.Y.[Qing-Yu],
Adeli, E.[Ehsan],
Zaharchuk, G.[Greg],
Pohl, K.M.[Kilian M.],
Disentangling Normal Aging From Severity of Disease via Weak
Supervision on Longitudinal MRI,
MedImg(41), No. 10, October 2022, pp. 2558-2569.
IEEE DOI
2210
Diseases, Magnetic resonance imaging, Aging, Trajectory, Training,
Supervised learning, cognitive impairment
BibRef
Aghaei, A.[Atefe],
Moghaddam, M.E.[Mohsen Ebrahimi],
Malek, H.[Hamed],
Interpretable ensemble deep learning model for early detection of
Alzheimer's disease using local interpretable model-agnostic
explanations,
IJIST(32), No. 6, 2022, pp. 1889-1902.
DOI Link
2212
Alzheimer's disease, ensemble deep learning, Inception-V3,
ResNet-50, structural MRI, transfer learning
BibRef
Xu, J.X.[Jia-Xing],
Bian, Q.T.[Qing-Tian],
Li, X.H.[Xin-Hang],
Zhang, A.[Aihu],
Ke, Y.P.[Yi-Ping],
Qiao, M.[Miao],
Zhang, W.[Wei],
Sim, W.K.J.[Wei Khang Jeremy],
Gulyás, B.[Balázs],
Contrastive Graph Pooling for Explainable Classification of Brain
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MedImg(43), No. 9, September 2024, pp. 3292-3305.
IEEE DOI Code:
WWW Link.
2409
BibRef
And:
Correction:
MedImg(43), No. 11, November 2024, pp. 4075-4075.
IEEE DOI
2411
Functional magnetic resonance imaging, Feature extraction,
Task analysis, Data mining, Alzheimer's disease, Message passing,
graph neural network
BibRef
Illakiya, T.,
Karthik, R.,
A deep feature fusion network with global context and
cross-dimensional dependencies for classification of mild cognitive
impairment from brain MRI,
IVC(144), 2024, pp. 104967.
Elsevier DOI
2404
Mild cognitive impairment, Magnetic resonance imaging, Deep learning,
Convolutional neural network, Classification: Alzheimer's disease
BibRef
Xu, J.H.[Jing-Hao],
Yuan, C.X.[Chen-Xi],
Ma, X.C.[Xiao-Chuan],
Shang, H.F.[Hui-Fang],
Shi, X.S.[Xiao-Shuang],
Zhu, X.F.[Xiao-Feng],
Interpretable medical deep framework by logits-constraint attention
guiding graph-based multi-scale fusion for Alzheimer's disease
analysis,
PR(152), 2024, pp. 110450.
Elsevier DOI Code:
WWW Link.
2405
Alzheimer's disease, Attention, Graph neural networks,
Multi-scale feature fusion, Structural MRI
See also Discussion on Interpretable medical deep framework by logits-constraint attention guiding graph-based multi-scale fusion for Alzheimer's disease analysis.
BibRef
Han, K.[Kangfu],
Li, G.[Gang],
Fang, Z.W.[Zhi-Wen],
Yang, F.[Feng],
Multi-Template Meta-Information Regularized Network for Alzheimer's
Disease Diagnosis Using Structural MRI,
MedImg(43), No. 5, May 2024, pp. 1664-1676.
IEEE DOI
2405
Feature extraction, Metadata, Self-supervised learning,
Mutual information, Alzheimer's disease, Aging, Minimization
BibRef
Khojaste-Sarakhsi, M.,
Haghighi, S.S.[Seyedhamidreza Shahabi],
Fatemi Ghomi, S.M.T.,
Marchiori, E.[Elena],
A 3D multi-scale CycleGAN framework for generating synthetic PETs
from MRIs for Alzheimer's disease diagnosis,
IVC(146), 2024, pp. 105017.
Elsevier DOI
2405
Cycle GAN, Multi-scale GAN, 3D image-to-image translation,
Image synthesis, Alzheimer's Disease diagnosis
BibRef
Hu, Y.[Yan],
Wang, J.[Jun],
Zhu, H.[Hao],
Li, J.C.[Jun-Cheng],
Shi, J.[Jun],
Cost-Sensitive Weighted Contrastive Learning Based on Graph
Convolutional Networks for Imbalanced Alzheimer's Disease Staging,
MedImg(43), No. 9, September 2024, pp. 3126-3136.
IEEE DOI
2409
Self-supervised learning, Vectors, Training data, Prototypes,
Feature extraction, Training, Optical fibers, rs-fMRI
BibRef
Manochandar, T.,
Diderot, P.K.[P. Kumaraguru],
Deep Learning-Based Magnetic Resonance Image Segmentation and
Classification for Alzheimer's Disease Diagnosis,
IJIG(25), No. 3, May 2025, pp. 2550026.
DOI Link
2505
BibRef
Rahim, N.[Nasir],
Ahmad, N.[Naveed],
Ullah, W.[Waseem],
Bedi, J.[Jatin],
Jung, Y.[Younhyun],
Early progression detection from MCI to AD using multi-view MRI for
enhanced assisted living,
IVC(157), 2025, pp. 105491.
Elsevier DOI Code:
WWW Link.
2504
Enhanced assisted living, Alzheimer's disease,
Deep learning models, Ensemble learning, Explainable AI
BibRef
Guo, X.[Xutao],
Ye, C.[Chenfei],
Zhang, M.K.[Ming-Kai],
Hao, X.Y.[Xing-Yu],
Yang, Y.[Yanwu],
Yu, Y.[Yue],
Ma, T.[Ting],
Han, Y.[Ying],
A Structure-Preserving Denoising Diffusion Model for AV45 PET
Quantification Without MRI in Alzheimer's Disease Diagnosis,
IJIST(35), No. 3, 2025, pp. e70074.
DOI Link
2506
Alzheimer's disease, AV45 PET quantification, diffusion model, MRI
BibRef
Khan, A.N.[Areeba Naseem],
Bilal, M.[Mohsin],
Khan, S.U.[Sajid Ullah],
Khan, S.[Salabat],
Sharif, M.[Muhammad],
Innovative MRI Denoising Using Federated and Transfer Learning,
IJIST(35), No. 3, 2025, pp. e70106.
DOI Link
2506
Alzheimer's disease, deep learning, diagnostic accuracy,
federated learning, healthcare data privacy, image quality, VGG16
BibRef
Yan, J.L.[Jie-Long],
Ying, S.H.[Shi-Hui],
Du, S.Y.[Shao-Yi],
Gao, Y.[Yue],
Graph Quality Matters on Revealing the Semantics Behind the Data in
Physical World,
PAMI(48), No. 3, March 2026, pp. 2236-2252.
IEEE DOI
2602
Complexity theory, Semantics, Social networking (online),
Medical diagnosis, Alzheimer's disease, Mutual information,
graph homophily
BibRef
Wang, T.X.[Tian-Xiang],
Dai, Q.[Qun],
Lu, H.[Han],
CE-AH: A contrast-enhanced attention hierarchical network for
Alzheimer's disease diagnosis based on structural MRI,
PR(169), 2026, pp. 111986.
Elsevier DOI
2509
Alzheimer's disease (AD), Contrastive learning, Attention mechanism,
Group normalization, Structural magnetic resonance imaging (sMRI)
BibRef
Hechkel, W.[Wided],
Missaoui, R.[Rim],
Helali, A.[Abdelhamid],
Leo, M.[Marco],
Hybrid CNN and SVM model for Alzheimer's disease classification using
categorical focal loss function,
PRL(199), 2026, pp. 261-268.
Elsevier DOI
2512
p
Alzheimer's disease (AD), Early diagnosis, MRI,
Convolutional neural network (CNN), Reduced complexity
BibRef
Trigui, S.[Sana],
Bezine, H.[Hala],
DuoViT-AD: A dual-scale vision transformer for Alzheimer's disease
detection from brain MRI,
PRL(203), 2026, pp. 133-138.
Elsevier DOI
2604
Alzheimer's disease, Vision transformer, Attention mechanism,
MRI, Deep learning, Model fusion
BibRef
Garg, A.[Ankit],
Shaw, R.[Rabi],
Siamese Capsule Network (SNNCap): Cognitive Analysis for Alzheimer's
Disease Classification From MRI Data,
IP(35), 2026, pp. 4149-4160.
IEEE DOI
2605
Filtering, MIMICs, Millimeter wave integrated circuits,
Monolithic integrated circuits, Feedback, Filters, Routing,
Siamese neural network (SNN)
BibRef
Timir, C.S.[Chakraborty Sudeepta],
Shankar, A.[Achyut],
Das, S.[Sanchali],
Viriyasitavat, W.[Wattana],
Optimized hybrid deep learning architecture for robust Alzheimer's
disease diagnosis using SMOTE-based data augmentation,
IVC(173), 2026, pp. 106060.
Elsevier DOI
2607
Alzheimer's disease, Hybrid deep learning,
Vision transformer (ViT), Swin transformer, MRI analysis
BibRef
Huang, Y.A.[Yu-An],
Hu, Y.[Yao],
Li, Y.C.[Yue-Chao],
Cao, X.[Xiyue],
Li, X.[Xinyuan],
Tan, K.C.[Kay Chen],
You, Z.H.[Zhu-Hong],
Huang, Z.A.[Zhi-An],
scBIT: Integrating Single-Cell Transcriptomic Data Into fMRI-Based
Prediction for Alzheimer's Disease Diagnosis,
MedImg(45), No. 7, July 2026, pp. 3424-3437.
IEEE DOI Code:
WWW Link.
2607
Functional magnetic resonance imaging, Imaging, Transcriptomics,
Neuroimaging, Gene expression, Brain modeling, Bioinformatics,
cross-modal data integration
BibRef
Kumar, S.[Suraj],
Singh, N.P.[Narendra Pratap],
Brahma, B.[Banalaxmi],
AI-Based Model for Detection and Classification of Alzheimer Disease,
ICCVMI23(1-6)
IEEE DOI
2403
Training, Support vector machines, Neurological diseases,
Magnetic resonance imaging, Computational modeling, MRI
BibRef
Ayyar, M.P.[Meghna P.],
Benois-Pineau, J.[Jenny],
Zemmari, A.[Akka],
Catheline, G.[Gwenaelle],
Explaining 3D CNNs for Alzheimer's Disease Classification on sMRI
Images with Multiple ROIs,
ICIP21(284-288)
IEEE DOI
2201
Heating systems, Deep learning, Correlation,
Magnetic resonance imaging, Image processing,
Deep Learning understanding
BibRef
Ebrahimi, A.,
Luo, S.,
Chiong, R.,
Introducing Transfer Leaming to 3D ResNet-18 for Alzheimer's Disease
Detection on MRI Images,
IVCNZ20(1-6)
IEEE DOI
2012
Training, Solid modeling,
Magnetic resonance imaging, Computational modeling, Taguchi
BibRef
Ben-Ahmed, O.,
Lecellier, F.,
Paccalin, M.,
Fernandez-Maloigne, C.,
Multi-View Visual Saliency-Based MRI Classification for Alzheimer's
Disease Diagnosis,
IPTA17(1-6)
IEEE DOI
1804
biomedical MRI, brain, diseases, image classification,
learning (artificial intelligence), medical image processing,
visual saliency
BibRef
Lazli, L.,
Boukadoum, M.,
Aďt-Mohamed, O.,
Brain Tissue Classification of Alzheimer Disease Using Partial Volume
Possibilistic Modeling: Application to ADNI Phantom Images,
IPTA17(1-5)
IEEE DOI
1804
biological tissues, biomedical MRI, brain, diseases,
fuzzy set theory, image classification, image denoising,
Possibilistic c-means algorithm
BibRef
Li, Q.[Qing],
Wu, X.[Xia],
Xu, L.[Lele],
Yao, L.[Li],
Chen, K.W.[Ke-Wei],
Multi-Feature Kernel Discriminant Dictionary Learning for
Classification in Alzheimer's Disease,
DICTA17(1-6)
IEEE DOI
1804
biomedical MRI, diseases, face recognition, feature extraction,
image classification, medical image processing,
Training
See also Multi-Feature Kernel Discriminant Dictionary Learning for Face Recognition.
BibRef
Shams-Baboli, A.,
Ezoji, M.,
A Zernike moment based method for classification of Alzheimer's
disease from structural MRI,
IPRIA17(38-43)
IEEE DOI
1712
backpropagation, biomedical MRI, diseases, feature extraction,
image classification, medical image processing, neural nets,
mild cognitive impairment
BibRef
Aderghal, K.[Karim],
Boissenin, M.[Manuel],
Benois-Pineau, J.[Jenny],
Catheline, G.[Gwenaëlle],
Afdel, K.[Karim],
Classification of sMRI for AD Diagnosis with Convolutional Neuronal
Networks: A Pilot 2-D+ epsilon Study on ADNI,
MMMod17(I: 690-701).
Springer DOI
1701
BibRef
Andersen, S.K.[Simon Kragh],
Jakobsen, C.E.[Christian Elmholt],
Pedersen, C.H.[Claus Hougaard],
Rasmussen, A.M.[Anders Munk],
Plocharski, M.[Maciej],
Řstergaard, L.R.[Lasse Riis],
Classification of Alzheimer's Disease from MRI Using Sulcal Morphology,
SCIA15(103-113).
Springer DOI
1506
BibRef
Cattell, L.[Liam],
Schnabel, J.A.[Julia A.],
Declerck, J.[Jerome],
Hutton, C.[Chloe],
Combined PET-MR Brain Registration to Discriminate between Alzheimer's
Disease and Healthy Controls,
WBIR14(134-143).
Springer DOI
1407
BibRef
Sun, Z.[Zhuo],
Jasinschi, R.S.[Radu S.],
Veerman, J.A.C.[Jan A.C.],
A new method for data-driven multi-brain atlas generation,
ICIP14(3503-3507)
IEEE DOI
1502
Alzheimer's disease
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Earlier: A1, A3, A2:
A method for detecting interstructural atrophy correlation in MRI brain
images,
ICIP12(1253-1256).
IEEE DOI
1302
BibRef
Mizotin, M.[Maxim],
Benois-Pineau, J.[Jenny],
Allard, M.[Michele],
Catheline, G.[Gwenaelle],
Feature-based brain MRI retrieval for Alzheimer disease diagnosis,
ICIP12(1241-1244).
IEEE DOI
1302
BibRef
Dyrba, M.[Martin],
Ewers, M.[Michael],
Wegrzyn, M.[Martin],
Kilimann, I.[Ingo],
Plant, C.[Claudia],
Oswald, A.[Annahita],
Meindl, T.[Thomas],
Pievani, M.[Michela],
Bokde, A.L.W.[Arun L. W.],
Fellgiebel, A.[Andreas],
Filippi, M.[Massimo],
Hampel, H.[Harald],
Kloppel, S.[Stefan],
Hauenstein, K.[Karlheinz],
Kirste, T.[Thomas],
Teipel, S.J.[Stefan J.],
Combining DTI and MRI for the Automated Detection of Alzheimer's
Disease Using a Large European Multicenter Dataset,
MBIA12(18-28).
Springer DOI
1210
BibRef
Veerman, J.A.C.,
Soldea, O.,
Sahindrakar, P.,
Wan, Y.,
Jasinschi, R.S.,
Application of computational anatomy methods to MRI data for the
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ICIP11(1593-1596).
IEEE DOI
1201
BibRef
Long, X.J.[Xiao-Jing],
Wyatt, C.[Chris],
An automatic unsupervised classification of MR images in Alzheimer's
disease,
CVPR10(2910-2917).
IEEE DOI
1006
BibRef
Soldea, O.[Octavian],
Ekin, A.[Ahmet],
Soldea, D.F.[Diana F.],
Unay, D.[Devrim],
Cetin, M.[Mujdat],
Ercil, A.[Aytul],
Uzunbas, M.G.[Mustafa Gokhan],
Firat, Z.[Zeynep],
Cihangiroglu, M.[Mutlu],
Initiative, T.A.D.N.[The Alzheimers Disease Neuroimaging],
Segmentation of Anatomical Structures in Brain MR Images Using Atlases
in FSL: A Quantitative Approach,
ICPR10(2592-2595).
IEEE DOI
1008
BibRef
dos Santos, W.P.[Wellington P.],
de Souza, R.E.[Ricardo E.],
Silva, A.F.D.[Ascendino F. D.],
Santos Filho, P.B.[Plínio B.],
Evaluation of Alzheimer's Disease by Analysis of MR Images Using
Multilayer Perceptrons, Polynomial Nets and Kohonen LVQ Classifiers,
MIRAGE07(12-22).
Springer DOI
0703
BibRef
Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Brain, Parkinson's Disease .