{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T06:56:54Z","timestamp":1792652214679,"version":"4.5.0"},"reference-count":48,"publisher":"Elsevier BV","issue":"1","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:00:00Z","timestamp":1765497600000},"content-version":"am","delay-in-days":345,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["clinicalkey.fr","clinicalkey.jp","redjournal.org","clinicalkey.es","clinicalkey.com.au","clinicalkey.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Radiation Oncology*Biology*Physics"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1016\/j.ijrobp.2024.07.2149","type":"journal-article","created":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T23:46:03Z","timestamp":1722987963000},"page":"230-240","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":27,"title":["Auto-delineation of Treatment Target Volume for Radiation Therapy Using Large Language Model-Aided Multimodal Learning"],"prefix":"10.1016","volume":"121","author":[{"given":"Praveenbalaji","family":"Rajendran","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yizheng","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Niedermayr","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Buyyounouski","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hilary","family":"Bagshaw","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nataliya","family":"Kovalchuk","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuejun","family":"Gu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steven","family":"Hancock","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Xing","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianjin","family":"Dai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0001","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.meddos.2005.12.004","article-title":"Overview of image-guided radiation therapy","volume":"31","author":"Xing","year":"2006","journal-title":"Med Dosim"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0002","first-page":"239","article-title":"Radiation therapy for cancer","volume":"3","author":"Jaffray","year":"2015","journal-title":"Cancer"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0003","doi-asserted-by":"crossref","first-page":"1121","DOI":"10.1016\/S0360-3016(00)00518-6","article-title":"The probability of correct target dosage: Dose-population histograms for deriving treatment margins in radiotherapy","volume":"47","author":"Van Herk","year":"2000","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0004","doi-asserted-by":"crossref","DOI":"10.1126\/scitranslmed.3005148","article-title":"New paradigms and future challenges in radiation oncology: An update of biological targets and technology","volume":"5","author":"Liauw","year":"2013","journal-title":"Sci Transl Med"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0005","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.radonc.2016.09.009","article-title":"Uncertainties in volume delineation in radiation oncology: A systematic review and recommendations for future studies","volume":"121","author":"Vinod","year":"2016","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0006","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.clon.2020.10.017","article-title":"Structure and processes of existing practice in radiotherapy peer review: a systematic review of the literature","volume":"33","author":"Lewis","year":"2021","journal-title":"Clin Oncol"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0007","first-page":"1","article-title":"Analysis of a real time group consensus peer review process in radiation oncology: an evaluation of effectiveness and feasibility","volume":"13","author":"Albert","year":"2018","journal-title":"Rad Oncol"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0008","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.ijrobp.2016.09.015","article-title":"Does peer review of radiation plans affect clinical care? A systematic review of the literature","volume":"97","author":"Brunskill","year":"2017","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0009","doi-asserted-by":"crossref","first-page":"2341","DOI":"10.1007\/s12094-020-02394-8","article-title":"100% peer review in radiation oncology: is it feasible?","volume":"22","author":"Martin-Garcia","year":"2020","journal-title":"Clin Trans Oncol"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0010","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1002\/mp.12045","article-title":"Segmentation of organs-at-risks in head and neck ct images using convolutional neural networks","volume":"44","author":"Ibragimov","year":"2017","journal-title":"Med Phys"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0011","doi-asserted-by":"crossref","first-page":"5862","DOI":"10.1002\/mp.15146","article-title":"Automated delineation of head and neck organs at risk using synthetic mri-aided mask scoring regional convolutional neural network","volume":"48","author":"Dai","year":"2021","journal-title":"Med Phys"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0012","doi-asserted-by":"crossref","first-page":"7063","DOI":"10.1002\/mp.15264","article-title":"Synthetic ct-aided multiorgan segmentation for CBCT-guided adaptive pancreatic radiotherapy","volume":"48","author":"Dai","year":"2021","journal-title":"Med Phys"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0013","doi-asserted-by":"crossref","first-page":"1822","DOI":"10.1109\/TMI.2018.2806309","article-title":"Automatic multi-organ segmentation on abdominal ct with dense v-networks","volume":"37","author":"Gibson","year":"2018","journal-title":"IEEE Trans Med Imaging"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0014","article-title":"Segmentation of the prostate and organs at risk in male pelvic ct images using deep learning","volume":"4","author":"Kazemifar","year":"2018","journal-title":"Biomed Phys Eng Exp"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0015","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/j.radonc.2019.03.004","article-title":"Rapid advances in auto-segmentation of organs at risk and target volumes in head and neck cancer","volume":"135","author":"Kosmin","year":"2019","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0016","doi-asserted-by":"crossref","first-page":"480","DOI":"10.1038\/s42256-019-0099-z","article-title":"Clinically applicable deep learning framework for organs at risk delineation in ct images","volume":"1","author":"Tang","year":"2019","journal-title":"Nat Mach Intell"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0017","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1016\/j.ijrobp.2019.02.040","article-title":"Deep learning-based delineation of head and neck organs at risk: geometric and dosimetric evaluation","volume":"104","author":"van Rooij","year":"2019","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0018","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1148\/radiol.2018181432","article-title":"Automated abdominal segmentation of ct scans for body composition analysis using deep learning","volume":"290","author":"Weston","year":"2019","journal-title":"Radiology"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0019","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.radonc.2019.09.022","article-title":"Improving automatic delineation for head and neck organs at risk by deep learning contouring","volume":"142","author":"Van Dijk","year":"2020","journal-title":"Radiother Oncol"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0020","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2023.1213068","article-title":"A clinical evaluation of the performance of five commercial artificial intelligence contouring systems for radiotherapy","volume":"13","author":"Doolan","year":"2023","journal-title":"Front Oncol"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0021","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.compmedimag.2018.03.001","article-title":"An application of cascaded 3D fully convolutional networks for medical image segmentation","volume":"66","author":"Roth","year":"2018","journal-title":"Comput Med Imaging Graph"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0022","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1088\/0031-9155\/57\/6\/1527","article-title":"Automatic computer-aided detection of prostate cancer based on multiparametric magnetic resonance image analysis","volume":"57","author":"Vos","year":"2012","journal-title":"Phys Med Biol"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0023","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1186\/s12911-023-02289-y","article-title":"Cnn-res: deep learning framework for segmentation of acute ischemic stroke lesions on multimodal mri images","volume":"23","author":"Gheibi","year":"2023","journal-title":"BMC Med Inform Decis Mak"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0024","doi-asserted-by":"crossref","first-page":"6421","DOI":"10.1002\/mp.14517","article-title":"Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch unet","volume":"47","author":"Chen","year":"2020","journal-title":"Med Phys"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0025","series-title":"2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI)","first-page":"735","article-title":"Link of transformers in CV and NLP: A brief survey","author":"Jia","year":"2022"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0026","series-title":"2020 15th Conference on Computer Science and Information Systems (FedCSIS)","first-page":"179","article-title":"Overview of the transformer-based models for nlp tasks","author":"Gillioz","year":"2020"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0027","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2023.106126","article-title":"Vision transformers in medical computer vision\u2014a contemplative retrospection","volume":"122","author":"Parvaiz","year":"2023","journal-title":"Eng Appl Artif Intell"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0028","doi-asserted-by":"crossref","first-page":"5625","DOI":"10.1109\/TPAMI.2024.3369699","article-title":"Vision-language models for vision tasks: a survey","volume":"46","author":"Zhang","year":"2024","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0029","article-title":"Contextual object detection with multimodal large language models","author":"Zang","year":"2023","journal-title":"arXiv preprint arXiv:230518279"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0030","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"11686","article-title":"Cris: clip-driven referring image segmentation","author":"Wang","year":"2022"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0031","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"18155","article-title":"Lavt: language-aware vision transformer for referring image segmentation","author":"Yang","year":"2022"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0032","doi-asserted-by":"crossref","first-page":"7900","DOI":"10.1109\/TPAMI.2022.3217852","article-title":"Vlt: vision-language transformer and query generation for referring segmentation","volume":"45","author":"Ding","year":"2023","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0033","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"22236","article-title":"Robust referring video object segmentation with cyclic structural consensus","author":"Li","year":"2023"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0034","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"15506","article-title":"Encoder fusion network with co-attention embedding for referring image segmentation","author":"Feng","year":"2021"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0035","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"10012","article-title":"Swin transformer: Hierarchical vision transformer using shifted windows","author":"Liu","year":"2021"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0036","article-title":"Gpt-4 technical report","author":"Achiam","year":"2023","journal-title":"arXiv preprint arXiv:230308774"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0037","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3458754","article-title":"Domain-specific language model pretraining for biomedical natural language processing","volume":"3","author":"Gu","year":"2022","journal-title":"ACM Trans Comput Healthc"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0038","series-title":"Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images. International MICCAI Brainlesion Workshop","first-page":"272","author":"Hatamizadeh","year":"2021"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0039","first-page":"32","article-title":"Pytorch: An imperative style, high-performance deep learning library","author":"Paszke","year":"2019","journal-title":"Adv Neural Inf Process Syst"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0040","article-title":"Huggingface's transformers: state-of-the-art natural language processing","author":"Wolf","year":"2019","journal-title":"arXiv preprint arXiv:191003771"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0041","article-title":"Monai: An open-source framework for deep learning in healthcare","author":"Cardoso","year":"2022","journal-title":"arXiv preprint arXiv:221102701"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0042","series-title":"Atrial Segmentation and LV Quantification Challenges: 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018","first-page":"371","article-title":"Left-ventricle quantification using residual u-net. Statistical Atlases and Computational Models of the Heart","author":"Kerfoot","year":"2019"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0043","doi-asserted-by":"crossref","first-page":"1107","DOI":"10.1016\/j.ijrobp.2018.01.057","article-title":"Radiomic biomarkers to refine risk models for distant metastasis in hpv-related oropharyngeal carcinoma","volume":"102","author":"Kwan","year":"2018","journal-title":"Int J Radiat Oncol Biol Phys"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0044","article-title":"Data from radiomic biomarkers to refine risk models for distant metastasis in oropharyngeal carcinoma","author":"Kwan","year":"2019","journal-title":"Cancer Imaging Arch"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0045","doi-asserted-by":"crossref","first-page":"1045","DOI":"10.1007\/s10278-013-9622-7","article-title":"The cancer imaging archive (tcia): maintaining and operating a public information repository","volume":"26","author":"Clark","year":"2013","journal-title":"J Digit Imaging"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0046","doi-asserted-by":"crossref","first-page":"1471","DOI":"10.1245\/s10434-010-0985-4","article-title":"The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM","volume":"17","author":"Edge","year":"2010","journal-title":"Ann Surg Oncol"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0047","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1186\/s13104-022-06096-y","article-title":"Towards a guideline for evaluation metrics in medical image segmentation","volume":"15","author":"M\u00fcller","year":"2022","journal-title":"BMC Res Notes"},{"key":"10.1016\/j.ijrobp.2024.07.2149_bib0048","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2021.104497","article-title":"Comparison of metrics for the evaluation of medical segmentations using prostate mri dataset","volume":"134","author":"Nai","year":"2021","journal-title":"Comput Biol Med"}],"container-title":["International Journal of Radiation Oncology*Biology*Physics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360301624029717?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360301624029717?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,3,10]],"date-time":"2025-03-10T23:33:46Z","timestamp":1741649626000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0360301624029717"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1]]},"references-count":48,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["S0360301624029717"],"URL":"https:\/\/doi.org\/10.1016\/j.ijrobp.2024.07.2149","relation":{},"ISSN":["0360-3016"],"issn-type":[{"value":"0360-3016","type":"print"}],"subject":[],"published":{"date-parts":[[2025,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Auto-delineation of Treatment Target Volume for Radiation Therapy Using Large Language Model-Aided Multimodal Learning","name":"articletitle","label":"Article Title"},{"value":"International Journal of Radiation Oncology*Biology*Physics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ijrobp.2024.07.2149","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}