Work

Semi-Supervised Learning of MRI Synthesis Without Fully-Sampled Ground Truths

Year: 2022

Type: article

Source: IEEE Transactions on Medical Imaging

DOI: 10.1109/tmi.2022.3199155

Authors: Mahmut Yurt, Onat Dalmaz, Salman Dar, Muzaffer Ozbey, Berk Tinaz, Kader Oguz, Tolga Cukur

Institutions: Bilkent University, Stanford University, University of Southern California, Hacettepe University

Language: English

Topic: Advanced MRI Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

Funders: Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, Türkiye Bilimler Akademisi, Bilim Akademisi

Award: Çoklu Kontrast Manyetik Rezonans GörüntülemedeGeriçatım ve Sentez için Derin Öğrenme Teknikleri

OpenAlex ID: W4291653333

FWCI: 4.006

Cites: 69

Cited by: 36

Related to: 10