@article{Boon_AI_Radiotherapy_2018,
    title = {{Assessing the Role of Artificial Intelligence (AI) in Clinical Oncology: Utility of Machine Learning in Radiotherapy Target Volume Delineation}},
    year = {2018},
    journal = {Medicines},
    author = {Boon, Ian and Au Yong, Tracy and Boon, Cheng},
    number = {4},
    month = {12},
    pages = {131},
    volume = {5},
    publisher = {MDPI AG},
    doi = {10.3390/medicines5040131},
    issn = {2305-6320},
    pmid = {30544901}
}

@inproceedings{Kamath_ASTRA_2023,
    title = {{ASTRA: Atomic Surface Transformations for Radiotherapy Quality Assurance}},
    year = {2023},
    booktitle = {45th Annual International Conference of the IEEE Engineering in Medicine {\textbackslash}{\&} Biology Society (EMBC)},
    author = {Kamath, Amith and Poel, Robert and Willmann, Jonas and Ermis, Ekin and Andratschke, Nicolaus and Reyes, Mauricio},
    month = {7},
    url = {https://github.com/amithjkamath/astra},
    address = {Sydney},
    doi = {10.1109/EMBC40787.2023.10341062},
    keywords = {Automated Quality Assurance, Deep Learning, Index Terms-Radiotherapy, Treatment Planning, U-Net}
}

@article{Arbelle2019,
    title = {{QANet -- Quality Assurance Network for Image Segmentation}},
    year = {2019},
    author = {Arbelle, Assaf and Elul, Eliav and Raviv, Tammy Riklin},
    pages = {1--8},
    url = {http://arxiv.org/abs/1904.08503},
    issn = {2331-8422},
    arxivId = {1904.08503}
}

@article{Stupp_Radiotherapy_2005,
    title = {{Radiotherapy plus Concomitant and Adjuvant Temozolomide for Glioblastoma}},
    year = {2005},
    journal = {The New England Journal of Medicine},
    author = {Stupp, Roger and Mason, Warren P and Van Den Bent, Martin J and Weller, Michael and Fisher, Barbara and Taphoorn, Martin J B and Belanger, Karl and Brandes, Alba A and Marosi, Christine and Bogdahn, Ulrich and Curschmann, Jürgen and Janzer, Robert C and Ludwin, Samuel K and Gorlia, Thierry and Allgeier, Anouk and Lacombe, Denis and Cairncross, J Gregory and Eisenhauer, Elizabeth and Mirimanoff, René O},
    number = {10},
    month = {3},
    pages = {987--996},
    volume = {352},
    url = {www.nejm.org}
}

@article{Poel2021a,
    title = {{The predictive value of segmentation metrics on dosimetry in organs at risk of the brain}},
    year = {2021},
    journal = {Medical Image Analysis},
    author = {Poel, Robert and R{\"{u}}fenacht, Elias and Hermann, Evelyn and Scheib, Stefan and Manser, Peter and Aebersold, Daniel M. and Reyes, Mauricio},
    pages = {102161},
    volume = {73},
    publisher = {Elsevier B.V.},
    url = {https://doi.org/10.1016/j.media.2021.102161},
    doi = {10.1016/j.media.2021.102161},
    issn = {13618423},
    pmid = {34293536},
    keywords = {Automatic segmentation, Brain OARs, Clinical validation, Dose distribution, Radiotherapy, Segmentation parameters}
}

@article{RodriguezOuteiral2023ASegmentations,
    title = {{A network score-based metric to optimize the quality assurance of automatic radiotherapy target segmentations}},
    year = {2023},
    journal = {Physics and Imaging in Radiation Oncology},
    author = {Rodr{\'{i}}guez Outeiral, Roque and Ferreira Silv{\'{e}}rio, Nicole and Gonz{\'{a}}lez, Patrick J. and Schaake, Eva E. and Janssen, Tomas and van der Heide, Uulke A. and Simões, Rita},
    month = {10},
    volume = {28},
    publisher = {Elsevier Ireland Ltd},
    doi = {10.1016/j.phro.2023.100500},
    issn = {24056316},
    keywords = {Automatic segmentation, Cervical cancer, Confidence estimation, Quality assurance, Rectal cancer}
}

@misc{Nguyen2022AdvancesPlanning,
    title = {{Advances in Automated Treatment Planning}},
    year = {2022},
    booktitle = {Seminars in Radiation Oncology},
    author = {Nguyen, Dan and Lin, Mu Han and Sher, David and Lu, Weiguo and Jia, Xun and Jiang, Steve},
    number = {4},
    month = {10},
    pages = {343--350},
    volume = {32},
    publisher = {W.B. Saunders},
    doi = {10.1016/j.semradonc.2022.06.004},
    issn = {15329461},
    pmid = {36202437}
}

@article{Das2009AnalysisTherapy,
    title = {{Analysis of Treatment Planning Time Among Systems and Planners for Intensity-Modulated Radiation Therapy}},
    year = {2009},
    journal = {Journal of the American College of Radiology},
    author = {Das, Indra J. and Moskvin, Vadim and Johnstone, Peter A.},
    number = {7},
    pages = {514--517},
    volume = {6},
    publisher = {Elsevier},
    doi = {10.1016/j.jacr.2008.12.013},
    issn = {15461440},
    keywords = {Intensity-modulated radiation therapy, manpower issues, treatment planning, treatment time}
}

@article{KoflerAreCoefficient,
    title = {{Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient}},
    journal = {Journal of Machine Learning for Biomedical Imaging},
    author = {Kofler, Florian and Ezhov, Ivan and Isensee, Fabian and Balsiger, Fabian and Berger, Christoph and Koerner, Maximilian and Demiray, Beatrice and Rackerseder, Julia and Paetzold, Jo-Hannes and Li, Hongwei and Shit, Suprosanna and Mckinley, Richard and Piraud, Marie and Bakas, Spyridon and Zimmer, Claus and Navab, Nassir and Kirschke, Jan and Wiestler, Benedikt and Menze, Bjoern},
    pages = {27--71},
    volume = {2023},
    url = {https://melba-journal.org/2023:002},
    keywords = {MR, biomedical image analyis 28 Are we using appropriate segmentation metrics?, deep learning, glioma, interpretation, machine learning, metrics, segmentation}
}

@article{Henderson2022AutomaticLearning,
    title = {{Automatic identification of segmentation errors for radiotherapy using geometric learning}},
    year = {2022},
    author = {Henderson, Edward G. A. and Green, Andrew F. and van Herk, Marcel and Osorio, Eliana M. Vasquez},
    month = {6},
    url = {http://arxiv.org/abs/2206.13317},
    arxivId = {2206.13317}
}

@article{Teng2024Beam-wiseRadiotherapy,
    title = {{Beam-wise dose composition learning for head and neck cancer dose prediction in radiotherapy}},
    year = {2024},
    journal = {Medical Image Analysis},
    author = {Teng, Lin and Wang, Bin and Xu, Xuanang and Zhang, Jiadong and Mei, Lanzhuju and Feng, Qianjin and Shen, Dinggang},
    month = {2},
    volume = {92},
    publisher = {Elsevier B.V.},
    doi = {10.1016/j.media.2023.103045},
    issn = {13618423},
    pmid = {38071865},
    keywords = {Beam-wise dose learning, Dose prediction, Dose-volume histogram, Head and neck cancer, Radiation therapy}
}

@misc{McFaline-Figueroa2018BrainTumors,
    title = {{Brain Tumors}},
    year = {2018},
    booktitle = {American Journal of Medicine},
    author = {McFaline-Figueroa, J. Ricardo and Lee, Eudocia Q.},
    number = {8},
    month = {8},
    pages = {874--882},
    volume = {131},
    publisher = {Elsevier Inc.},
    doi = {10.1016/j.amjmed.2017.12.039},
    issn = {15557162},
    pmid = {29371158},
    keywords = {Brain metastases, Brain tumor, Cerebral edema, Glioblastoma, Meningioma, Seizures}
}

@article{Peters2010Critical02.02,
    title = {{Critical impact of radiotherapy protocol compliance and quality in the treatment of advanced head and neck cancer: Results from TROG 02.02}},
    year = {2010},
    journal = {Journal of Clinical Oncology},
    author = {Peters, Lester J. and O'Sullivan, Brian and Giralt, Jordi and Fitzgerald, Thomas J. and Trotti, Andy and Bernier, Jacques and Bourhis, Jean and Yuen, Kally and Fisher, Richard and Rischin, Danny},
    number = {18},
    month = {6},
    pages = {2996--3001},
    volume = {28},
    doi = {10.1200/JCO.2009.27.4498},
    issn = {0732183X},
    pmid = {20479390}
}

@misc{Sahiner2019DeepTherapy,
    title = {{Deep learning in medical imaging and radiation therapy}},
    year = {2019},
    booktitle = {Medical Physics},
    author = {Sahiner, Berkman and Pezeshk, Aria and Hadjiiski, Lubomir M. and Wang, Xiaosong and Drukker, Karen and Cha, Kenny H. and Summers, Ronald M. and Giger, Maryellen L.},
    number = {1},
    month = {1},
    pages = {e1-e36},
    volume = {46},
    publisher = {John Wiley and Sons Ltd},
    doi = {10.1002/mp.13264},
    issn = {24734209},
    pmid = {30367497},
    keywords = {computer-aided detection/characterization, deep learning, machine learning, reconstruction, segmentation, treatment}
}

@article{Poel2023Deep-Learning-BasedContouring,
    title = {{Deep-Learning-Based Dose Predictor for Glioblastoma–Assessing the Sensitivity and Robustness for Dose Awareness in Contouring}},
    year = {2023},
    journal = {Cancers},
    author = {Poel, Robert and Kamath, Amith J. and Willmann, Jonas and Andratschke, Nicolaus and Ermi{\c{s}}, Ekin and Aebersold, Daniel M. and Manser, Peter and Reyes, Mauricio},
    number = {17},
    month = {9},
    volume = {15},
    publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
    doi = {10.3390/cancers15174226},
    issn = {20726694},
    keywords = {VMAT, deep learning, dose prediction, glioblastoma, quality assurance, radiotherapy}
}

@article{Roberfroid2024DIVE-ART:Therapy,
    title = {{DIVE-ART: A tool to guide clinicians towards dosimetrically informed volume editions of automatically segmented volumes in adaptive radiation therapy}},
    year = {2024},
    journal = {Radiotherapy and Oncology},
    author = {Roberfroid, Benjamin and Lee, John A. and Geets, Xavier and Sterpin, Edmond and Barrag{\'{a}}n-Montero, Ana M.},
    month = {3},
    pages = {110108},
    volume = {192},
    url = {https://linkinghub.elsevier.com/retrieve/pii/S016781402400029X},
    doi = {10.1016/j.radonc.2024.110108},
    issn = {01678140}
}

@article{Niyazi2023ESTRO-EANOGlioblastoma,
    title = {{ESTRO-EANO guideline on target delineation and radiotherapy details for glioblastoma}},
    year = {2023},
    journal = {Radiotherapy and Oncology},
    author = {Niyazi, Maximilian and Andratschke, Nicolaus and Bendszus, Martin and Chalmers, Anthony J. and Erridge, Sara C. and Galldiks, Norbert and Lagerwaard, Frank J. and Navarria, Pierina and Munck af Rosensch{\"{o}}ld, Per and Ricardi, Umberto and van den Bent, Martin J. and Weller, Michael and Belka, Claus and Minniti, Giuseppe},
    month = {7},
    volume = {184},
    publisher = {Elsevier Ireland Ltd},
    doi = {10.1016/j.radonc.2023.109663},
    issn = {18790887},
    pmid = {37059335},
    keywords = {Delineation, EANO, ESTRO, Glioblastoma, Radiotherapy, Target volume}
}

@inproceedings{Cubero2023ExploringSegmentation,
    title = {{Exploring Uncertainty for Clinical Acceptability in Head and Neck Deep Learning-Based OAR Segmentation}},
    year = {2023},
    booktitle = {Proceedings - International Symposium on Biomedical Imaging},
    author = {Cubero, L. and Serrano, J. and Castelli, J. and De Crevoisier, R. and Acosta, O. and Pascau, J.},
    volume = {2023-April},
    publisher = {IEEE Computer Society},
    isbn = {9781665473583},
    doi = {10.1109/ISBI53787.2023.10230442},
    issn = {19458452},
    keywords = {Deep learning, automated segmentation, head and neck radiotherapy, organ at risk, uncertainty}
}

@inproceedings{Kamath2023HowSegmentation,
    title = {{How Sensitive are Deep Learning Based Dose Prediction Models to Variability in Organs at Risk Segmentation?}},
    year = {2023},
    booktitle = {International Symposium on Biomedical Imaging},
    author = {Kamath, Amith and Poel, Robert and Willmann, Jonas and Andratschke, Nicolaus and Reyes, Mauricio},
    keywords = {Automated Dose Prediction, Deep Learning, Index Terms-Radiotherapy, Treatment Planning, U-Net}
}

@article{Strolin2023HowImages,
    title = {{How smart is artificial intelligence in organs delineation? Testing a CE and FDA-approved Deep-Learning tool using multiple expert contours delineated on planning CT images}},
    year = {2023},
    journal = {Frontiers in Oncology},
    author = {Strolin, Silvia and Santoro, Miriam and Paolani, Giulia and Ammendolia, Ilario and Arcelli, Alessandra and Benini, Anna and Bisello, Silvia and Cardano, Raffaele and Cavallini, Letizia and Deraco, Elisa and Donati, Costanza Maria and Galietta, Erika and Galuppi, Andrea and Guido, Alessandra and Ferioli, Martina and Laghi, Viola and Medici, Federica and Ntreta, Maria and Razganiayeva, Natalya and Siepe, Giambattista and Tolento, Giorgio and Vallerossa, Daria and Zamagni, Alice and Morganti, Alessio Giuseppe and Strigari, Lidia},
    volume = {13},
    publisher = {Frontiers Media S.A.},
    doi = {10.3389/FONC.2023.1089807/FULL},
    issn = {2234943X},
    keywords = {deep learning tool, independent external validation, quality metrics, segmentation, time saved}
}

@article{Harrison2022MachinePlanning,
    title = {{Machine Learning for Auto-Segmentation in Radiotherapy Planning}},
    year = {2022},
    journal = {Clinical Oncology},
    author = {Harrison, K. and Pullen, H. and Welsh, C. and Oktay, O. and Alvarez-Valle, J. and Jena, R.},
    number = {2},
    month = {2},
    pages = {74--88},
    volume = {34},
    publisher = {Elsevier Ltd},
    doi = {10.1016/j.clon.2021.12.003},
    issn = {14332981},
    pmid = {34996682},
    keywords = {Auto-segmentation, Deep learning, Machine learning, Radiotherapy planning}
}

@article{Babier2021OpenKBP:Dataset,
    title = {{OpenKBP: The open-access knowledge-based planning grand challenge and dataset}},
    year = {2021},
    journal = {Medical Physics},
    author = {Babier, Aaron and Zhang, Binghao and Mahmood, Rafid and Moore, Kevin L. and Purdie, Thomas G. and McNiven, Andrea L. and Chan, Timothy C.Y.},
    number = {9},
    month = {9},
    pages = {5549--5561},
    volume = {48},
    publisher = {John Wiley and Sons Ltd},
    doi = {10.1002/mp.14845},
    issn = {24734209},
    pmid = {34156719},
    keywords = {automated planning, computer vision, equity, diversity, and inclusion, knowledge-based planning, machine learning, public dataset}
}

@article{Rufenacht2023PyRaDiSe:Conversion,
    title = {{PyRaDiSe: A Python package for DICOM-RT-based auto-segmentation pipeline construction and DICOM-RT data conversion}},
    year = {2023},
    journal = {Computer Methods and Programs in Biomedicine},
    author = {R{\"{u}}fenacht, Elias and Kamath, Amith and Suter, Yannick and Poel, Robert and Ermi{\c{s}}, Ekin and Scheib, Stefan and Reyes, Mauricio},
    month = {4},
    volume = {231},
    publisher = {Elsevier Ireland Ltd},
    doi = {10.1016/j.cmpb.2023.107374},
    issn = {18727565},
    pmid = {36738608},
    keywords = {87.53.Tf, 89.70.+c, Auto-segmentation, DICOM, DICOM RT structure sets, DICOM RTSS conversion, Deep learning, Radiotherapy}
}

@misc{Claessens2022QualityTherapy,
    title = {{Quality Assurance for AI-Based Applications in Radiation Therapy}},
    year = {2022},
    booktitle = {Seminars in Radiation Oncology},
    author = {Claessens, Michaël and Oria, Carmen Seller and Brouwer, Charlotte L. and Ziemer, Benjamin P. and Scholey, Jessica E. and Lin, Hui and Witztum, Alon and Morin, Olivier and Naqa, Issam El and Van Elmpt, Wouter and Verellen, Dirk},
    number = {4},
    month = {10},
    pages = {421--431},
    volume = {32},
    publisher = {W.B. Saunders},
    doi = {10.1016/j.semradonc.2022.06.011},
    issn = {15329461},
    pmid = {36202444}
}

@article{Hui2018QualityApproach,
    title = {{Quality assurance tool for organ at risk delineation in radiation therapy using a parametric statistical approach}},
    year = {2018},
    journal = {Medical Physics},
    author = {Hui, Cheukkai B. and Nourzadeh, Hamidreza and Watkins, William T. and Trifiletti, Daniel M. and Alonso, Clayton E. and Dutta, Sunil W. and Siebers, Jeffrey V.},
    number = {5},
    month = {5},
    pages = {2089--2096},
    volume = {45},
    publisher = {John Wiley and Sons Ltd},
    doi = {10.1002/mp.12835},
    issn = {24734209},
    pmid = {29481703},
    keywords = {OAR, delineation, normal tissue, quality assurance, segmentation}
}

@article{Valindria2017ReverseTruth,
    title = {{Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth}},
    year = {2017},
    author = {Valindria, Vanya V. and Lavdas, Ioannis and Bai, Wenjia and Kamnitsas, Konstantinos and Aboagye, Eric O. and Rockall, Andrea G. and Rueckert, Daniel and Glocker, Ben},
    month = {2},
    url = {http://arxiv.org/abs/1702.03407},
    arxivId = {1702.03407}
}

@misc{Scaringi2018TechnicalTumors,
    title = {{Technical advances in radiation therapy for brain tumors}},
    year = {2018},
    booktitle = {Anticancer Research},
    author = {Scaringi, Claudia and Agolli, Linda and Minniti, Giuseppe},
    number = {11},
    month = {11},
    pages = {6041--6045},
    volume = {38},
    publisher = {International Institute of Anticancer Research},
    doi = {10.21873/anticanres.12954},
    issn = {17917530},
    pmid = {30396918},
    keywords = {Brain tumors, Conformal radiotherapy, IGRT, IMRT, Proton therapy, Review, Stereotactic radiosurgery, VMAT}
}

@article{Liu2021TechnicalRadiotherapy,
    title = {{Technical Note: A cascade 3D U-Net for dose prediction in radiotherapy}},
    year = {2021},
    journal = {Medical Physics},
    author = {Liu, Shuolin and Zhang, Jingjing and Li, Teng and Yan, Hui and Liu, Jianfei},
    number = {9},
    month = {9},
    pages = {5574--5582},
    volume = {48},
    publisher = {John Wiley and Sons Ltd},
    doi = {10.1002/mp.15034},
    issn = {24734209},
    pmid = {34101852}
}

@article{VanEsch2006TestingCalculation,
    title = {{Testing of the analytical anisotropic algorithm for photon dose calculation}},
    year = {2006},
    journal = {Medical Physics},
    author = {Van Esch, Ann and Tillikainen, Laura and Pyykkonen, Jukka and Tenhunen, Mikko and Helminen, Hannu and Siljam{\"{a}}ki, Sami and Alakuijala, Jyrki and Paiusco, Marta and Iori, Mauro and Huyskens, Dominique P.},
    number = {11},
    pages = {4130--4148},
    volume = {33},
    publisher = {John Wiley and Sons Ltd},
    doi = {10.1118/1.2358333},
    issn = {00942405},
    pmid = {17153392}
}

@article{Xiao2022TransDose:MR-LINACs,
    title = {{TransDose: a transformer-based UNet model for fast and accurate dose calculation for MR-LINACs}},
    year = {2022},
    journal = {Physics in Medicine and Biology},
    author = {Xiao, Fan and Cai, Jiajun and Zhou, Xuanru and Zhou, Linghong and Song, Ting and Li, Yongbao},
    number = {12},
    month = {6},
    volume = {67},
    publisher = {Institute of Physics},
    doi = {10.1088/1361-6560/ac7376},
    issn = {13616560},
    pmid = {35613559},
    keywords = {MR-LINAC, adaptive radiotherapy, dose calculation, transformer}
}

@article{Podobnik2024VOARiability:Images,
    title = {{vOARiability: Interobserver and intermodality variability analysis in OAR contouring from head and neck CT and MR images}},
    year = {2024},
    journal = {Medical Physics},
    author = {Podobnik, Gašper and Ibragimov, Bulat and Peterlin, Primož and Strojan, Primož and Vrtovec, Tomaž},
    publisher = {John Wiley and Sons Ltd},
    doi = {10.1002/mp.16924},
    issn = {24734209},
    keywords = {computed tomography, contouring, head and neck cancer, image segmentation, magnetic resonance, organs-at-risk, radiotherapy, variability analysis}
}