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Deep learning-based outcome prediction using PET/CT and automatically predicted probability maps of primary tumor in patients with oropharyngeal cancer.

A. Biase, B. Ma, J. Guo, L. van Dijk, J. Langendijk, S. Both, P. van Ooijen, and N. Sijtsema. Comput. Methods Programs Biomed., (2024)

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Stefan Both

Rüdiger Both

Friedhelm Böth

Dietmar Both

Ralf Both

Other publications of authors with the same name

TransRP: Transformer-based PET/CT feature extraction incorporating clinical data for recurrence-free survival prediction in oropharyngeal cancer.B. Ma, J. Guo, L. van Dijk, P. van Ooijen, S. Both, and N. Sijtsema. MIDL, volume 227 of Proceedings of Machine Learning Research, page 1640-1654. PMLR, (2023)SynthRAD2023 Grand Challenge dataset: generating synthetic CT for radiotherapy.A. Thummerer, E. van der Bijl, A. Galapon, J. Verhoeff, J. Langendijk, S. Both, C. van den Berg, and M. Maspero. CoRR, (2023)Deep Learning and Radiomics Based PET/CT Image Feature Extraction from Auto Segmented Tumor Volumes for Recurrence-Free Survival Prediction in Oropharyngeal Cancer Patients.B. Ma, Y. Li, H. Chu, W. Tang, L. la O. Arévalo, J. Guo, P. van Ooijen, S. Both, J. Langendijk, L. van Dijk and 1 other author(s). HECKTOR@MICCAI, volume 13626 of Lecture Notes in Computer Science, page 240-254. Springer, (2022)Deep learning-based outcome prediction using PET/CT and automatically predicted probability maps of primary tumor in patients with oropharyngeal cancer.A. Biase, B. Ma, J. Guo, L. van Dijk, J. Langendijk, S. Both, P. van Ooijen, and N. Sijtsema. Comput. Methods Programs Biomed., (2024)Computer-assisted targeted therapy (CATT) for prostate radiotherapy planning by fusion of CT and MRI.J. Chappelow, S. Both, S. Viswanath, S. Hahn, M. Feldman, M. Rosen, J. Tomaszewski, N. Vapiwala, P. Patel, and A. Madabhushi. Medical Imaging: Image-Guided Procedures, volume 7625 of SPIE Proceedings, page 76252C. SPIE, (2010)Swin UNETR for Tumor and Lymph Node Segmentation Using 3D PET/CT Imaging: A Transfer Learning Approach.H. Chu, L. la O. Arévalo, W. Tang, B. Ma, Y. Li, A. Biase, S. Both, J. Langendijk, P. van Ooijen, N. Sijtsema and 1 other author(s). HECKTOR@MICCAI, volume 13626 of Lecture Notes in Computer Science, page 114-120. Springer, (2022)Linked statistical shape models for multi-modal segmentation: application to prostate CT-MR segmentation in radiotherapy planning.N. Chowdhury, J. Chappelow, R. Toth, S. Kim, S. Hahn, N. Vapiwala, H. Lin, S. Both, and A. Madabhushi. Medical Imaging: Computer-Aided Diagnosis, volume 7963 of SPIE Proceedings, page 796314. SPIE, (2011)Self-supervised Multi-modality Image Feature Extraction for the Progression Free Survival Prediction in Head and Neck Cancer.B. Ma, J. Guo, A. Biase, N. Sourlos, W. Tang, P. van Ooijen, S. Both, and N. Sijtsema. HECKTOR@MICCAI, volume 13209 of Lecture Notes in Computer Science, page 308-317. Springer, (2021)

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Disambiguation of "Both, Stefan"

Please choose a person to relate this publication to

Stefan Both

Rüdiger Both

Friedhelm Böth

Dietmar Both

Ralf Both

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Both, Stefan"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Deep learning-based outcome prediction using PET/CT and automatically predicted probability maps of primary tumor in patients with oropharyngeal cancer.

Please choose a person to relate this publication to

Stefan Both

Rüdiger Both

Friedhelm Böth

Dietmar Both

Ralf Both

Other publications of authors with the same name

Disambiguation