Comparison of computed tomography image features extracted by radiomics, self-supervised learning and end-to-end deep learning for outcome prediction of oropharyngeal cancer-Reference-Cited by-同舟云学术

Comparison of computed tomography image features extracted by radiomics, self-supervised learning and end-to-end deep learning for outcome prediction of oropharyngeal cancer

Published:2023-10 Issue: Volume:28 Page:100502
ISSN:2405-6316
Container-title:Physics and Imaging in Radiation Oncology
language:en
Short-container-title:Physics and Imaging in Radiation Oncology

Author:

Ma Baoqiang^ORCID,Guo Jiapan,Chu Hung,van Dijk Lisanne V.,van Ooijen Peter M.A.^ORCID,Langendijk Johannes A.,Both Stefan,Sijtsema Nanna M.^ORCID

Funder

University Medical Centre Groningen

Rijksuniversiteit Groningen

China Scholarship Council

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,Radiation

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