Identification of mild cognitive impairment using multimodal 3D imaging data and graph convolutional networks

被引：0
|
作者：
Liang, Shengbin [1 ]
Chen, Tingting [1 ]
Ma, Jinfeng [1 ]
Ren, Shuanglong [1 ]
Lu, Xixi [1 ]
Du, Wencai [2 ]
机构：
[1] School of Software, Henan University, Kaifeng,475004, China
[2] Institute for Data Engineering and Science, University of Saint Joseph, Macau,999078, China
来源：
Physics in Medicine and Biology | 2024年 / 69卷 / 23期
关键词：
Positron emission tomography;
D O I：
10.1088/1361-6560/ad8c94
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [21] Generating 3D Faces using Multi-column Graph Convolutional Networks
    Li, Kun
    Liu, Jingying
    Lai, Yu-Kun
    Yang, Jingyu
    COMPUTER GRAPHICS FORUM, 2019, 38 (07) : 215 - 224
  • [22] Ensemble of 3D densely connected convolutional network for diagnosis of mild cognitive impairment and Alzheimer's disease
    Wang, Hongfei
    Shen, Yanyan
    Wang, Shuqiang
    Xiao, Tengfei
    Deng, Liming
    Wang, Xiangyu
    Zhao, Xinyan
    NEUROCOMPUTING, 2019, 333 : 145 - 156
  • [23] TREE SPECIES IDENTIFICATION USING 3D SPECTRAL DATA AND 3D CONVOLUTIONAL NEURAL NETWORK
    Polonen, Ilkka
    Annala, Leevi
    Rahkonen, Samuli
    Nevalainen, Olli
    Honkavaara, Eija
    Tuominen, Sakari
    Viljanen, Niko
    Hakala, Teemu
    2018 9TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS), 2018,
  • [24] Classification of Mild Cognitive Impairment With Multimodal Data Using Both Labeled and Unlabeled Samples
    Yuan, Shaoxun
    Li, Haitao
    Wu, Jiansheng
    Sun, Xiao
    IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2021, 18 (06) : 2281 - 2290
  • [25] Scaled Subprofile Modeling and Convolutional Neural Networks for the Identification of Parkinson's Disease in 3D Nuclear Imaging Data
    Manzanera, Octavio Martinez
    Meles, Sanne K.
    Leenders, Klaus L.
    Renken, Remco J.
    Pagani, Marco
    Arnaldi, Dario
    Nobili, Flavio
    Obeso, Jose
    Rodriguez Oroz, Maria
    Morbelli, Silvia
    Maurits, Natasha M.
    INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 2019, 29 (09)
  • [26] Semantic Graph Convolutional Networks for 3D Human Pose Regression
    Zhao, Long
    Peng, Xi
    Tian, Yu
    Kapadia, Mubbasir
    Metaxas, Dimitris N.
    2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019), 2019, : 3420 - 3430
  • [27] 3D ACTION RECOGNITION USING DATA VISUALIZATION AND CONVOLUTIONAL NEURAL NETWORKS
    Liu, Mengyuan
    Chen, Chen
    Liu, Hong
    2017 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME), 2017, : 925 - 930
  • [28] Segmentation Improves 3D Object Classification in Graph Convolutional Networks
    Holzhueter, Clara
    Teich, Florian
    Woergoetter, Florentin
    PROCEEDINGS OF THE 17TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISAPP), VOL 4, 2022, : 290 - 298
  • [29] Compositional Graph Convolutional Networks for 3D Human Pose Estimation
    Zou, Zhiming
    Liu, Tianqi
    Wu, Dapeng
    Tang, Wei
    2021 16TH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION (FG 2021), 2021,
  • [30] Dense graph convolutional neural networks on 3D meshes for 3D object segmentation and classification
    Tang, Wenming
    Qiu, Guoping
    IMAGE AND VISION COMPUTING, 2021, 114
12345