Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics.

Autor: Huynh, Bao Ngoc, Groendahl, Aurora Rosvoll, Tomic, Oliver, Liland, Kristian Hovde, Knudtsen, Ingerid Skjei, Hoebers, Frank, van Elmpt, Wouter, Malinen, Eirik, Dale, Einar, Futsaether, Cecilia Marie

Publikováno v: Frontiers in Medicine; 2024, p1-20, 20p

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Deep learning-based auto-delineation of gross tumour volumes and involved nodes in PET/CT images of head and neck cancer patients.

Autor: Moe, Yngve Mardal¹ (AUTHOR), Groendahl, Aurora Rosvoll¹ (AUTHOR), Tomic, Oliver¹ (AUTHOR), Dale, Einar² (AUTHOR), Malinen, Eirik^3,4 (AUTHOR), Futsaether, Cecilia Marie¹ (AUTHOR) cecilia.futsaether@nmbu.no

Publikováno v: European Journal of Nuclear Medicine & Molecular Imaging. Aug2021, Vol. 48 Issue 9, p2782-2792. 11p. 1 Color Photograph, 2 Diagrams, 3 Charts, 2 Graphs.

PET Normalizations to Improve Deep Learning Auto-Segmentation of Head and Neck Tumors in 3D PET/CT

Autor: Ren, Jintao, Huynh, Bao Ngoc, Groendahl, Aurora Rosvoll, Tomic, Oliver, Futsaether, Cecilia Marie, Korreman, Stine Sofia

Publikováno v: Ren, J, Huynh, B N, Groendahl, A R, Tomic, O, Futsaether, C M & Korreman, S S 2022, PET Normalizations to Improve Deep Learning Auto-Segmentation of Head and Neck Tumors in 3D PET/CT . in V Andrearczyk, V Oreiller, M Hatt & A Depeursinge (eds), Head and Neck Tumor Segmentation and Outcome Prediction-2nd Challenge, HECKTOR 2021, Held in Conjunction with MICCAI 2021, Proceedings . Springer Science and Business Media Deutschland GmbH, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13209 LNCS, pp. 83-91, 2nd 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2021, held in conjunction with 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, Virtual, Online, 27/09/2021 . https://doi.org/10.1007/978-3-030-98253-9_7

Auto-segmentation of head and neck cancer (HNC) primary gross tumor volume (GTVt) is a necessary but challenging process for radiotherapy treatment planning and radiomics studies. The HEad and neCK TumOR Segmentation Challenge (HECKTOR) 2021 comprise

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