Use of deep learning-based radiomics to differentiate Parkinson’s disease patients from normal controls: a study based on [18F]FDG PET imaging

被引：0
|
作者：
Xiaoming Sun
Jingjie Ge
Lanlan Li
Qi Zhang
Wei Lin
Yue Chen
Ping Wu
Likun Yang
Chuantao Zuo
Jiehui Jiang
机构：
[1] Shanghai University,Institute of Biomedical Engineering, School of Communication and Information Engineering
[2] Fudan University,PET Center, Huashan Hospital
[3] 904 Hospital of PLA,Department of Neurosurgery
[4] Nuclear Medicine and Molecular Imaging Key Laboratory of Sichuan Province,Department of Nuclear Medicine, Affiliated Hospital of Southwest Medical University
[5] National Center for Neurological Disorder,undefined
来源：
European Radiology | 2022年 / 32卷
关键词：
Deep learning radiomics; Parkinson’s disease; [; F]fluorodeoxyglucose PET; Support vector machine;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：8008 / 8018
页数：10
相关论文
共 50 条
  • [1] Use of deep learning-based radiomics to differentiate Parkinson's disease patients from normal controls: a study based on [18F]FDG PET imaging
    Sun, Xiaoming
    Ge, Jingjie
    Li, Lanlan
    Zhang, Qi
    Lin, Wei
    Chen, Yue
    Wu, Ping
    Yang, Likun
    Zuo, Chuantao
    Jiang, Jiehui
    EUROPEAN RADIOLOGY, 2022, 32 (11) : 8008 - 8018
  • [2] Deep-Learning Radiomics for Discrimination Conversion of Alzheimer's Disease in Patients With Mild Cognitive Impairment: A Study Based on 18F-FDG PET Imaging
    Zhou, Ping
    Zeng, Rong
    Yu, Lun
    Feng, Yabo
    Chen, Chuxin
    Li, Fang
    Liu, Yang
    Huang, Yanhui
    Huang, Zhongxiong
    FRONTIERS IN AGING NEUROSCIENCE, 2021, 13
  • [3] [18F]Florbetapir PET Imaging in Cognitively Normal Parkinson's Disease
    Chen, Yin
    Nasrallah, Ilya
    Gross, Rachel Goldmann
    Akhtar, Rizwan
    Hurtig, Howard
    Chen-Plotkin, Alice
    Chahine, Lama
    Trojanowski, John
    Weintraub, Daniel
    Dubroff, Jacob
    JOURNAL OF NUCLEAR MEDICINE, 2015, 56 (03)
  • [4] Deep learning-based amyloid PET positivity classification model in the Alzheimer’s disease continuum by using 2-[18F]FDG PET
    Suhong Kim
    Peter Lee
    Kyeong Taek Oh
    Min Soo Byun
    Dahyun Yi
    Jun Ho Lee
    Yu Kyeong Kim
    Byoung Seok Ye
    Mi Jin Yun
    Dong Young Lee
    Yong Jeong
    EJNMMI Research, 11
  • [5] Deep learning-based amyloid PET positivity classification model in the Alzheimer's disease continuum by using 2-[18F]FDG PET
    Kim, Suhong
    Lee, Peter
    Oh, Kyeong Taek
    Byun, Min Soo
    Yi, Dahyun
    Lee, Jun Ho
    Kim, Yu Kyeong
    Ye, Byoung Seok
    Yun, Mi Jin
    Lee, Dong Young
    Jeong, Yong
    EJNMMI RESEARCH, 2021, 11 (01)
  • [6] [18F]FDG-PET imaging of supraspinal locomotor control in Parkinson's disease
    Zwergal, A.
    Grosch, M.
    Schoeberl, F.
    Levin, J.
    Boetzel, K.
    Schniepp, R.
    Wuehr, M.
    Dieterich, M.
    EUROPEAN JOURNAL OF NEUROLOGY, 2020, 27 : 67 - 67
  • [7] Deep learning-based combination of [18F]-FDG PET and CT images for producing pulmonary perfusion image
    Gu, Jiabing
    Qiu, Qingtao
    Zhu, Jian
    Cao, Qiang
    Hou, Zhen
    Li, Baosheng
    Shu, Huazhong
    MEDICAL PHYSICS, 2023, 50 (12) : 7779 - 7790
  • [8] Radiomics based on 2-[18F]FDG PET/CT can differentiate nonmetastatic gallbladder cancer and cholecystitis
    Han, Yun
    Pan, Yue
    Zhang, Jingfeng
    Li, Can
    Liu, Jiajin
    Wang, Yanmei
    Xu, Xiaodan
    Sun, Yabing
    Wang, Guanyun
    Xu, Baixuan
    CLINICAL AND TRANSLATIONAL IMAGING, 2024, 12 (06) : 639 - 649
  • [9] Deep learning based generation of high-count preclinical [18F]-FDG PET images from low-count [18F]-FDG PET images
    Dutta, Kaushik
    Whitehead, Timothy
    Laforest, Richard
    Jha, Abhinav
    Shoghi, Kooresh
    JOURNAL OF NUCLEAR MEDICINE, 2022, 63
  • [10] Metabolic brain networks in the Chinese patients with Parkinson's disease based on 18F-FDG PET imaging
    Wu, Ping
    Zhang, HuiWei
    Wang, Jian
    Zuo, Chuantao
    JOURNAL OF NUCLEAR MEDICINE, 2012, 53
12345