Phase Contrast Image Restoration by Formulating Its Imaging Principle and Reversing the Formulation With Deep Neural Networks-Reference-Cited by-同舟云学术

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Phase Contrast Image Restoration by Formulating Its Imaging Principle and Reversing the Formulation With Deep Neural Networks

Published:2023-04 Issue:4 Volume:42 Page:1068-1082
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Han Liang¹^ORCID,Su Hang²,Yin Zhaozheng³^ORCID

Affiliation:

1. Department of Computer Science, Stony Brook University, Stony Brook, NY, USA

2. Department of Computer Science and Technology, Tsinghua University, Beijing, China

3. Department of Computer Science, and the Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA

Funder

NSF CAREER

Stony Brook- Brookhaven National Laboratory Seed Grant

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Link

https://ieeexplore.ieee.org/ielam/42/10091712/9956861-aam.pdf

Reference90 articles.

1. Total variation based image restoration with free local constraints

2. Reliable deep-learning-based phase imaging with uncertainty quantification

3. Deterministic edge-preserving regularization in computed imaging

4. Real-time coherent diffraction inversion using deep generative networks

5. Discrete Total Variation: New Definition and Minimization

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Differential interference contrast phase edging net: an all-optical learning system for edge detection of phase objects;Chinese Optics Letters;2024

2. Histology Image Artifact Restoration with Lightweight Transformer Based Diffusion Model;Lecture Notes in Computer Science;2024

3. Artifact Detection and Restoration in Histology Images With Stain-Style and Structural Preservation;IEEE Transactions on Medical Imaging;2023-12

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