Work

A Universal Intensity Standardization Method Based on a Many-to-One Weak-Paired Cycle Generative Adversarial Network for Magnetic Resonance Images

Year: 2019

Type: article

Source: IEEE Transactions on Medical Imaging

DOI: 10.1109/tmi.2019.2894692

Authors: Yuan Gao, Yingchao Liu, Yuanyuan Wang, Zhifeng Shi, Jinhua Yu

Institutions: Fudan University, Shandong University, Shandong Provincial Hospital, Huashan Hospital

Language: English

Topic: Generative Adversarial Networks and Image Synthesis

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

Funder: National Key Research and Development Program of China

Awards: G2278590765, G5196763209

OpenAlex ID: W2914765210

FWCI: 2.891

Cites: 33

Cited by: 61

Related to: 10