sMRI-ADNet: an interpretable deep learning framework integrating Euclidean-graph representations of Alzheimer's disease solely from structural MRI.

Abstract

Authors

• Zhiwei Song
  Department of Infection Diseases, Xianju County People's Hospital, Taizhou, Zhejiang, China.
• Honglun Li
  Department of Medical Radiology, Affiliated Yantai Yuhuangding Hospital of Qingdao University Medical College, Yantai 264099, China. Electronic address: hlli_YHDhospital@hotmail.com.
• Yiyu Zhang
  School of Computer and Control Engineering, Yantai University, No. 30, Qingquan Road, Laishan District, Yantai City, 264005, Shandong Province, China.
• Chuanzhen Zhu
  School of Computer and Control Engineering, Yantai University, Yantai, 264005, China.
• Minbo Jiang
  School of Computer and Control Engineering, Yantai University, Yantai, 264005, China.
• Limei Song
  Tianjin Key Laboratory of Intelligent Control of Electrical Equipment, Tiangong University, Tianjin 300387, People's Republic of China. Electronic address: songlimei@tiangong.edu.cn.
• Yi Wang
  Department of Neurology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.
• Minhui Ouyang
  Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
• Fang Hu
  Key Laboratory of Medical Imaging and Artificial Intelligence of Hunan Province, Xiangnan University, Chenzhou, 423000, Hunan, China.
• Qiang Zheng
  First People's Hospital of Zunyi City, Zunyi, China.

Keywords

External Resources