Artificial Intelligence and Big Data in Radiation Oncology

2024

1. Jintao Ren, Muheng Li, Stine Sofia Korreman, “Sine Wave Normalization for Deep Learning-Based Tumor Segmentation in CT/PET Imaging”, arXiv:2409.13410, 2024, doi: 10.48550/arXiv.2409.13410.
2. Emma Skarsø Buhl, Else Maae, Louise Wichmann Matthiessen, Mette Holck Nielsen, Maja Maraldo, Mette Møller, Stine Elleberg, Sami Aziz-Jowad Al-Rawi, Birgitte Vrou Offersen, Stine Sofia Korreman, “Data harvesting vs data farming: A study of the importance of variation vs sample size in deep learning-based auto-segmentation for breast cancer patients”, arXiv:2404.03369, 2024, doi: 10.48550/arXiv.2404.03369.
3. Jintao Ren, Mathis Rasmussen, Jasper Nijkamp, Jesper Grau Eriksen, Stine Korreman, ”Segment anything model for head and neck tumor segmentation with CT, PET and MRI multi-modality images”, arXiv:2402.17454, 2024, doi: 10.48550/arXiv.2402.17454.
4. Emma Skarsø Buhl, Ebbe Laugaard Lorenzen, Lasse Refsgaard, Anders Winther Mølby Nielsen, Annette Thorbøl Lund Brixen, Else Maae, Hanne Spangsberg Holm, Joachim Schøler, Linh My Hoang Thai, Louise Wichmann Matthiessen, Maja Vestmø Maraldo, Mathias Maximiliano Nielsen, Marianne Besserman Johansen, Marie Louise Milo, Marie Benzon Mogensen, Mette Holck Nielsen, Mette Møller, Maja Voie Sand, Peter Pagh Schultz, Sami Aziz-Jowad Al-Rawi, Saskia Esser-Naumann, Sophie Yammeni, Stine Elleberg Petersen,  Birgitte Vrou Offersen, and Stine Sofia Korreman, “Development and comprehensive evaluation of a national DBCG consensus-based auto-segmentation model for lymph node levels in breast cancer radiotherapy”, accepted for publication in Radiotherapy and Oncology.
5. Ciaran Malone, Antony Carver, Christian Fiandra, Mark J. Gooding, Stine S. Korreman, Joana Matos Dias, Richard A. Popple, Humberto Rocha, Wouter Crijns, and Carlos E. Cardenas, “Is full-automation in radiotherapy treatment planning ready for take off?”, Radiotherapy and Oncology 110546, 2024, doi: 10.1016/j.radonc.2024.110546.
6. Kareem A. Wahid, Zaphanlene Y. Kaffey, David P. Farris, Laia Humbert-Vidan, Amy C. Moreno, Mathis Rasmussen, Jintao Ren, Mohamed A. Naser, Tucker J. Netherton, Stine Korreman, Guha Balakrishnan, Clifton D. Fuller, David Fuentes, and Michael J. Dohopolski, “Artificial Intelligence Uncertainty Quantification in Radiotherapy Applications - A Scoping Review”, Radiotherapy and Oncology 201:110542 , 2024, doi: 10.1016/j.radonc.2024.110542.
7. Mark J. Gooding, Shafak Aluwini, Teresa Guerrero Urbano, Yasmin McQuinlan, Deborah Om, Floor H E Staal, Tanguy Perennec, Sana Azzarouali, Carlos E. Cardenas, Antony Carver, Stine Sofia Korreman, and Jean-Emmanuel Bibault, “Fully Automated Radiotherapy Treatment Planning: A scan-to-plan challenge”, Radiotherapy and Oncology 200:110513, 2024, doi: 10.1016/j.radonc.2024.110513.
8. Jintao Ren, Jonas Teuwen, Jasper Nijkamp, Mathis Rasmussen, Zeno Gouw, Jesper Grau Eriksen, Jan-Jakob Sonke, and Stine Korreman, “Enhancing the reliability of deep learning-based head and neck tumour segmentation using uncertainty estimation with multi-modal images”, Physics in Medicine and Biology 69(16):165018, 2024, doi: 10.1088/1361-6560/ad682d.
9. Kim Møller Hochreuter, Jintao Ren, Jasper Nijkamp, Stine Sofia Korreman, Slávka Lukacova, Jesper Folsted Kallehauge, and Anouk Kirsten Trip, “The effect of mitigating inconsistencies in clinical delineations on deep-learning segmentation accuracy of the GTV in glioblastoma”, Physics in Imaging and Radiation Oncology 31:100620, 2024, doi: 10.1016/j.phro.2024.100620.
10. Mathis Ersted Rasmussen, Kamal Akbarov, Egor Titovich, Jasper Albertus Nijkamp, Wouter Van Elmpt, Hanne Primdahl, Pernille Lassen, Jon Cacicedo, Lisbeth Cordero-Mendez, A.F.M. Kamal Uddin, Ahmed Mohamed, Ben Prajogi, Kartika Erida Brohet, Catherine Nyongesa, Darejan Lomidze,  Gisupnikha Prasiko, Gustavo Ferraris, Humera Mahmood, Igor Stojkovski, Isa Isayev, Issa Mohamad, Leivon Shirley, Lotfi Kochbati, Ludmila Eftodiev, Maksim Piatkevich, Maria Matilde Bonilla Jara, Orges Spahiu, Rakhat Aralbayev, Raushan Zakirova, Sandya Subramaniam, Solomon Kibudde, Uranchimeg Tsegmed, Stine Sofia Korreman, and Jesper Grau Eriksen, “The potential of E-Learning interventions and AI-assisted contouring Skills in rAdiotherapy: The ELAISA study”, Journal of Clinical Oncology – Global Oncology 10:e2400173 , 2024, doi: 10.1200/GO.24.00173.
11. Andreas Smolders, Luciano Rivetti, Nadine Vatterodt, Stine S Korreman, Anthony Lomax, M Sharma, Andrej Studen, Damien C Weber, Robert Jeraj, and Francesca Albertini, “DiffuseRT: predicting likely anatomical deformations of patients undergoing radiotherapy”, Physics in Medicine and Biology 69(15):155016, 2024, doi: 10.1088/1361-6560/ad61b7.
12. Mathis Ersted Rasmussen, Casper Dueholm Vestergaard, Jesper Folsted Kallehauge, Jintao Ren, Maiken Haislund Guldberg, Ole Nørrevang, Ulrik Vindelev Elvstrøm, and Stine Sofia Korreman, ”RadDeploy: A framework for integrating in-house developed models seamlessly into radiotherapy workflows”, Physics in Imaging and Radiation Oncology 31:100607, 2024, doi: 10.1016/j.phro.2024.100607.
13. Coen Hurkmans, Jean-Emmanuel Bibault, Kristy K Brock, Wouter van Elmpt, Mary Feng, Clifton David Fuller, Barbara A Jereczek-Fossa, Stine Korreman, Guillaume Landry, Frederic Madesta, Charles Mayo, Alan McWilliam, Filipe Moura, Ludvig Paul Muren, Issam El Naqa, Jan Seuntjens, Vincenzo Valentini, and Michael Velec, “A joint ESTRO and AAPM guideline for development, clinical validation and reporting of artificial intelligence models in radiation therapy”, Radiotherapy and Oncology 197:110345, 2024, doi: 10.1016/j.radonc.2024.110345.
14. Lasse Refsgaard, Emma Skarsø Buhl, Esben Yates, Else Maae, Martin Berg, Sami Al-Rawi, Abhilasha Saini, Maja Vestmø Maraldo, Kristian Boye, Marie Louise Holm Milo, Ingelise Jensen, Louise Wichmann Matthiessen, Susanne Nørring Bekke, Mette Holck Nielsen, Ebbe Lorenzen, Lise Bech Jellesmark Thorsen, Stine Sofia Korreman, and Birgitte Vrou Offersen, “Evaluating Danish Breast Cancer Group locoregional radiotherapy guideline adherence in clinical treatment data 2008-2016: The DBCG RT Nation study”, Radiotherapy and Oncology 199:110289, 2024, doi: 10.1016/j.radonc.2024.110289.
15. Kareem A Wahid, Onur Sahin, Suprateek Kundu, Diana Lin, Anthony Alanis, Salik Tehami, Serageldin Kamel, Simon Duke, Michael V Sherer, Mathis Rasmussen, Stine Korreman, David Fuentes, Michael Cislo, Benjamin E Nelms, John P Christodouleas, James D Murphy, Abdallah SR Mohamed, Renjie He, Mohammed A Naser, Erin F Gillespie, and Clifton D Fuller, “Determining The Role Of Radiation Oncologist Demographic Factors On Segmentation Quality: Insights From A Crowd-Sourced Challenge Using Bayesian Estimation”, Journal of Clinical Oncology – Clinical Cancer Informatics vol 8:e2300174, 2024, doi: 10.1200/CCI.23.00174. (preprint on medRxiv doi: 10.1101/2023.08.30.23294786).