Deep Learning and Radiomics Based PET/CT Image Feature Extraction from Auto Segmented Tumor Volumes for Recurrence-Free Survival Prediction in Oropharyngeal Cancer Patients-Reference-Cited by-同舟云学术

Deep Learning and Radiomics Based PET/CT Image Feature Extraction from Auto Segmented Tumor Volumes for Recurrence-Free Survival Prediction in Oropharyngeal Cancer Patients

Published:2023 Issue: Volume: Page:240-254
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
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Author:

Ma Baoqiang,Li Yan,Chu Hung,Tang Wei,De la O Arévalo Luis Ricardo,Guo Jiapan,van Ooijen Peter,Both Stefan,Langendijk Johannes Albertus,van Dijk Lisanne V.,Sijtsema Nanna Maria

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-27420-6_24

Reference23 articles.

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3. Cramer, J.D., Burtness, B., Le, Q.T., Ferris, R.L.: The changing therapeutic landscape of head and neck cancer. Nat. Rev. Clin. Oncol. 16(11) (2019)

4. Lecture Notes in Computer Science;B Ma,2022

5. Zhai, T.T., et al.: The prognostic value of CT-based image-biomarkers for head and neck cancer patients treated with definitive (chemo-)radiation. Oral Oncol. 95 (2019)

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