3 papers
eess.IV2020
FISTA-Net: Learning A Fast Iterative Shrinkage Thresholding Network for Inverse Problems in Imaging
Jinxi Xiang, Yonggui Dong, Yunjie Yang
Inverse problems are essential to imaging applications. In this paper, we propose a model-based deep learning network, named FISTA-Net, by combining the merits of interpretability…
physics.app-ph2020
Image Reconstruction for Multi-frequency Electromagnetic Tomography based on Multiple Measurement Vector Model
Jinxi Xiang, Zhou Chen, Yonggui Dong +1
Imaging the bio-impedance distribution of a biological sample can provide understandings about the sample's electrical properties which is an important indicator of physiological s…
physics.app-ph2020
Multi-frequency Electromagnetic Tomography for Acute Stroke Detection Using Frequency Constrained Sparse Bayesian Learning
Jinxi Xiang, Yonggui Dong, Yunjie Yang
Imaging the bio-impedance distribution of the brain can provide initial diagnosis of acute stroke. This paper presents a compact and non-radiative tomographic modality, i.e. multi-…