538 related articles for article (PubMed ID: 31927305)
1. Region-of-Interest based sparse feature learning method for Alzheimer's disease identification.
Wang L; Liu Y; Zeng X; Cheng H; Wang Z; Wang Q
Comput Methods Programs Biomed; 2020 Apr; 187():105290. PubMed ID: 31927305
[TBL] [Abstract][Full Text] [Related]
2. Selecting the most relevant brain regions to discriminate Alzheimer's disease patients from healthy controls using multiple kernel learning: A comparison across functional and structural imaging modalities and atlases.
Rondina JM; Ferreira LK; de Souza Duran FL; Kubo R; Ono CR; Leite CC; Smid J; Nitrini R; Buchpiguel CA; Busatto GF
Neuroimage Clin; 2018; 17():628-641. PubMed ID: 29234599
[TBL] [Abstract][Full Text] [Related]
3. Analysis of structural brain MRI and multi-parameter classification for Alzheimer's disease.
Zhang Y; Liu S
Biomed Tech (Berl); 2018 Jul; 63(4):427-437. PubMed ID: 28622141
[TBL] [Abstract][Full Text] [Related]
4. Alzheimer's Disease Computer-Aided Diagnosis: Histogram-Based Analysis of Regional MRI Volumes for Feature Selection and Classification.
Ruiz E; Ramírez J; Górriz JM; Casillas J;
J Alzheimers Dis; 2018; 65(3):819-842. PubMed ID: 29966190
[TBL] [Abstract][Full Text] [Related]
5. Classification of Alzheimer's disease and prediction of mild cognitive impairment-to-Alzheimer's conversion from structural magnetic resource imaging using feature ranking and a genetic algorithm.
Beheshti I; Demirel H; Matsuda H;
Comput Biol Med; 2017 Apr; 83():109-119. PubMed ID: 28260614
[TBL] [Abstract][Full Text] [Related]
6. A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease.
Spasov S; Passamonti L; Duggento A; Liò P; Toschi N;
Neuroimage; 2019 Apr; 189():276-287. PubMed ID: 30654174
[TBL] [Abstract][Full Text] [Related]
7. A Classification Algorithm by Combination of Feature Decomposition and Kernel Discriminant Analysis (KDA) for Automatic MR Brain Image Classification and AD Diagnosis.
Elahifasaee F; Li F; Yang M
Comput Math Methods Med; 2019; 2019():1437123. PubMed ID: 32082407
[TBL] [Abstract][Full Text] [Related]
8. The Neuropsychological Correlates of Brain Perfusion and Gray Matter Volume in Alzheimer's Disease.
Tai H; Hirano S; Sakurai T; Nakano Y; Ishikawa A; Kojima K; Li H; Shimada H; Kashiwado K; Mukai H; Horikoshi T; Sugiyama A; Uno T; Kuwabara S
J Alzheimers Dis; 2020; 78(4):1639-1652. PubMed ID: 33185599
[TBL] [Abstract][Full Text] [Related]
9. Classification of Alzheimer's Disease and Mild Cognitive Impairment Based on Cortical and Subcortical Features from MRI T1 Brain Images Utilizing Four Different Types of Datasets.
Toshkhujaev S; Lee KH; Choi KY; Lee JJ; Kwon GR; Gupta Y; Lama RK
J Healthc Eng; 2020; 2020():3743171. PubMed ID: 32952988
[TBL] [Abstract][Full Text] [Related]
10. Automated atrophy assessment for Alzheimer's disease diagnosis from brain MRI images.
Shaikh TA; Ali R
Magn Reson Imaging; 2019 Oct; 62():167-173. PubMed ID: 31279772
[TBL] [Abstract][Full Text] [Related]
11. Improving Alzheimer's Disease Classification by Combining Multiple Measures.
Liu J; Wang J; Tang Z; Hu B; Wu FX; Pan Y
IEEE/ACM Trans Comput Biol Bioinform; 2018; 15(5):1649-1659. PubMed ID: 28749356
[TBL] [Abstract][Full Text] [Related]
12. Multi-Modality Sparse Representation for Alzheimer's Disease Classification.
Kwak K; Yun HJ; Park G; Lee JM;
J Alzheimers Dis; 2018; 65(3):807-817. PubMed ID: 29562503
[TBL] [Abstract][Full Text] [Related]
13. A novel joint HCPMMP method for automatically classifying Alzheimer's and different stage MCI patients.
Sheng J; Wang B; Zhang Q; Liu Q; Ma Y; Liu W; Shao M; Chen B
Behav Brain Res; 2019 Jun; 365():210-221. PubMed ID: 30836158
[TBL] [Abstract][Full Text] [Related]
14. Classification of Alzheimer's Disease Using Whole Brain Hierarchical Network.
Liu J; Li M; Lan W; Wu FX; Pan Y; Wang J
IEEE/ACM Trans Comput Biol Bioinform; 2018; 15(2):624-632. PubMed ID: 28114031
[TBL] [Abstract][Full Text] [Related]
15. Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry.
Sørensen L; Igel C; Pai A; Balas I; Anker C; Lillholm M; Nielsen M;
Neuroimage Clin; 2017; 13():470-482. PubMed ID: 28119818
[TBL] [Abstract][Full Text] [Related]
16. Combining viscoelasticity, diffusivity and volume of the hippocampus for the diagnosis of Alzheimer's disease based on magnetic resonance imaging.
Gerischer LM; Fehlner A; Köbe T; Prehn K; Antonenko D; Grittner U; Braun J; Sack I; Flöel A
Neuroimage Clin; 2018; 18():485-493. PubMed ID: 29527504
[TBL] [Abstract][Full Text] [Related]
17. Deep Learning for Alzheimer's Disease Classification using Texture Features.
So JH; Madusanka N; Choi HK; Choi BK; Park HG
Curr Med Imaging Rev; 2019; 15(7):689-698. PubMed ID: 32008517
[TBL] [Abstract][Full Text] [Related]
18. Alzheimer's Disease Diagnosis Based on Cortical and Subcortical Features.
Gupta Y; Lee KH; Choi KY; Lee JJ; Kim BC; Kwon GR
J Healthc Eng; 2019; 2019():2492719. PubMed ID: 30944718
[TBL] [Abstract][Full Text] [Related]
19. Canonical feature selection for joint regression and multi-class identification in Alzheimer's disease diagnosis.
Zhu X; Suk HI; Lee SW; Shen D
Brain Imaging Behav; 2016 Sep; 10(3):818-28. PubMed ID: 26254746
[TBL] [Abstract][Full Text] [Related]
20. Compartmental sparse feature selection method for Alzheimer's disease identification.
Yan Liu ; Ling Wang ; Xiangzhu Zeng ; Zheng Wang ; Yajun Gao ; Qiuyue Wang
Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul; 2017():3073-3076. PubMed ID: 29060547
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]