High-Dimensional Uncertainty Quantification in Electrical Impedance Tomography Forward Problem Based on Deep Neural Network-Reference-Cited by-同舟云学术

High-Dimensional Uncertainty Quantification in Electrical Impedance Tomography Forward Problem Based on Deep Neural Network

Author:

Zhao Yingge¹^ORCID,Wang Lingyue²,Li Ying²^ORCID,He Renjie³,Ma Chonglei⁴

Affiliation:

1. School of Intelligent Medical Engineering, Sanquan College, Xinxiang Medical University, Xinxiang, China

2. Hebei Key Laboratory of Bioelectromagnetic, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin, China

3. Department of Radiation Oncology, MD Anderson Cancer Center, Houston, USA

4. State Key Laboratory of Reliable and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, China

Funder

Natural Science Foundation of Hebei Province

Key Science and Technology Project of Henan Province

Outstanding Young Teachers Program of Sanquan College, Xinxiang Medical University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference39 articles.

1. Uncertainty quantification: Theory, implementation, and applications;hacken;Comput Rev,2016