{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T23:23:05Z","timestamp":1787872985756,"version":"build-2784847793"},"reference-count":49,"publisher":"IOP Publishing","issue":"17","license":[{"start":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T00:00:00Z","timestamp":1755648000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T00:00:00Z","timestamp":1755648000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001171","name":"Cancer Institute NSW","doi-asserted-by":"crossref","award":["TPG2165"],"award-info":[{"award-number":["TPG2165"]}],"id":[{"id":"10.13039\/501100001171","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"crossref","award":["1194004"],"award-info":[{"award-number":["1194004"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001111","name":"Cancer Australia","doi-asserted-by":"crossref","award":["1180776"],"award-info":[{"award-number":["1180776"]}],"id":[{"id":"10.13039\/501100001111","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2025,9,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>\n                  <jats:italic>Objective.<\/jats:italic> Head and neck (H&amp;N) volumetric imaging using a standard linear accelerator during treatment delivery could enable motion management strategies to improve geometric accuracy and avoid critical organs at risk (OARs). We developed a Kalman filter (KF) tracking approach to image 3D H&amp;N anatomy in real-time using 2D x-ray images. <jats:italic>Approach.<\/jats:italic> Our method produces a 3D image corresponding to each 2D projection at the time the projection is acquired. A KF incorporates 3D-to-2D projection geometry to weight the prior 3D deformable vector field (DVF) and 2D DVF measurement generated by registering each 2D x-ray image to a 2D image generated using the planning computed tomography (CT) image. We performed a simulation study using the planning CT image and 5 minute surface motion traces for 12 H&amp;N cancer patients. 2D intra-treatment images served as input to obtain the 3D DVF and resultant 3D images. We evaluated the KF tracking performance on the target and critical structures using centroid error, Hausdorff distance and Dice coefficient metrics. The results were compared to those from the current standard of care, no tracking. <jats:italic>Results.<\/jats:italic> Using KF tracking, we obtained a mean tumour centroid error of \u22120.2 \u00b1 0.6 mm, 0.3 \u00b1 0.8 mm, and 0.1 \u00b1 0.4 mm in the left\u2013right, anterior\u2013posterior and superior\u2013inferior axes respectively, compared to 0.9 \u00b1 1.0 mm, \u22120.8 \u00b1 1.1 mm, and \u22120.1 \u00b1 1.2 mm with no tracking. The 95th percentile Hausdorff distance for the tumour contour was 1.2 \u00b1 0.6 mm with KF tracking and 2.0 \u00b1 1.2 mm without tracking. The Dice coefficients were 0.91 \u00b1 0.08, 0.93 \u00b1 0.04, 0.93 \u00b1 0.05, 0.79 \u00b1 0.18, and 0.89 \u00b1 0.06 for the tumour, brainstem, left parotid gland, optic chiasm, and spinal cord respectively with KF tracking and 0.78 \u00b1 0.17, 0.84 \u00b1 0.06, 0.83 \u00b1 0.08, 0.39 \u00b1 0.14, and 0.70 \u00b1 0.13 respectively with no tracking. <jats:italic>Significance.<\/jats:italic> Volumetric imaging with a standard linear accelerator was investigated using KF tracking with H&amp;N patient data. The findings demonstrate accurate tracking of both the tumour and OARs, indicating potential applicability for the proposed method in a clinical translation setting.<\/jats:p>","DOI":"10.1088\/1361-6560\/adf371","type":"journal-article","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T22:51:31Z","timestamp":1753311091000},"page":"175006","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Volumetric imaging during head and neck radiation therapy using a Kalman filter tracking approach"],"prefix":"10.1088","volume":"70","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-6612-315X","authenticated-orcid":true,"given":"Chen","family":"Cheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4340-2547","authenticated-orcid":true,"given":"Mark","family":"Gardner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3002-384X","authenticated-orcid":true,"given":"Owen","family":"Dillon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0680-0693","authenticated-orcid":true,"given":"Youssef","family":"Ben Bouchta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9151-0150","authenticated-orcid":false,"given":"Purnima","family":"Sundaresan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4803-6507","authenticated-orcid":false,"given":"Paul","family":"Keall","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2025,8,20]]},"reference":[{"key":"pmbadf371bib1","doi-asserted-by":"publisher","first-page":"5458","DOI":"10.1109\/TIE.2012.2236994","article-title":"Industrial applications of the Kalman filter: a review","volume":"60","author":"Auger","year":"2013","journal-title":"IEEE Trans. Ind. Electron."},{"key":"pmbadf371bib2","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1016\/j.radonc.2014.03.024","article-title":"Estimating the demand for radiotherapy from the evidence: a review of changes from 2003 to 2012","volume":"112","author":"Barton","year":"2014","journal-title":"Radiother. Oncol."},{"key":"pmbadf371bib3","doi-asserted-by":"publisher","DOI":"10.1016\/j.phro.2024.100541","article-title":"The remove-the-mask open-source head and neck surface-guided radiation therapy system","volume":"29","author":"Ben Bouchta","year":"2024","journal-title":"Phys. Imaging Radiat. Oncol."},{"key":"pmbadf371bib4","doi-asserted-by":"publisher","DOI":"10.1088\/2057-1976\/2\/5\/055010","article-title":"TIGRE: a MATLAB-GPU toolbox for CBCT image reconstruction","volume":"2","author":"Biguri","year":"2016","journal-title":"Biomed. Phys. Eng. Express"},{"key":"pmbadf371bib5","doi-asserted-by":"publisher","first-page":"e803","DOI":"10.1016\/j.ijrobp.2010.12.015","article-title":"Dynamic MRI analysis of tumor and organ motion during rest and deglutition and margin assessment for radiotherapy of head-and-neck cancer","volume":"81","author":"Bradley","year":"2011","journal-title":"Int. J. Radiat. Oncol. Biol. Phys."},{"key":"pmbadf371bib6","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.radonc.2018.09.015","article-title":"Intrafraction motion quantification and planning target volume margin determination of head-and-neck tumors using cine magnetic resonance imaging","volume":"130","author":"Bruijnen","year":"2019","journal-title":"Radiother. Oncol."},{"key":"pmbadf371bib7","doi-asserted-by":"publisher","DOI":"10.1016\/j.adro.2022.100967","article-title":"Trajectory of anxiety related to radiation therapy mask immobilization and treatment delivery in head and neck cancer and radiation therapists\u2019 ability to detect this anxiety","volume":"7","author":"Burns","year":"2022","journal-title":"Adv. Radiat. Oncol."},{"key":"pmbadf371bib8","doi-asserted-by":"publisher","first-page":"4409","DOI":"10.1109\/TIE.2011.2162714","article-title":"Kalman filter for robot vision: a survey","volume":"59","author":"Chen","year":"2012","journal-title":"IEEE Trans. Ind. Electron."},{"key":"pmbadf371bib9","doi-asserted-by":"publisher","first-page":"5374","DOI":"10.21105\/joss.05374","article-title":"PlatiPy: processing library and analysis toolkit for medical imaging in python","volume":"8","author":"Chlap","year":"2023","journal-title":"J. Open Source Softw."},{"key":"pmbadf371bib10","doi-asserted-by":"publisher","first-page":"1095","DOI":"10.1016\/j.cviu.2013.02.009","article-title":"2D\/3D image registration using regression learning","volume":"117","author":"Chou","year":"2013","journal-title":"Comput. Vis. Image Underst."},{"key":"pmbadf371bib11","doi-asserted-by":"publisher","DOI":"10.1016\/j.adro.2023.101390","article-title":"Clinical experience of intrafractional motion monitoring of patients under head and neck radiation therapy using ExacTrac dynamic system","volume":"9","author":"Chow","year":"2024","journal-title":"Adv. Radiat. Oncol."},{"key":"pmbadf371bib12","doi-asserted-by":"publisher","first-page":"1334","DOI":"10.1002\/pon.1854","article-title":"Disruption to radiation therapy sessions due to anxiety among patients receiving radiation therapy to the head and neck area can be predicted using patient self-report measures","volume":"20","author":"Clover","year":"2011","journal-title":"Psycho-oncology"},{"key":"pmbadf371bib13","author":"Dahlquist","year":"2008"},{"key":"pmbadf371bib14","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/ab5539","article-title":"Soft-tissue prostate intrafraction motion tracking in 3D cine-MR for MR-guided radiotherapy","volume":"64","author":"de Muinck Keizer","year":"2019","journal-title":"Phys. Med. Biol."},{"key":"pmbadf371bib15","doi-asserted-by":"publisher","DOI":"10.1016\/j.phro.2024.100563","article-title":"Setup and intra-fractional motion measurements using surface scanning in head and neck cancer radiotherapy\u2013A feasibility study","volume":"29","author":"Essers","year":"2024","journal-title":"Phys. Imaging Radiat. Oncol."},{"key":"pmbadf371bib16","doi-asserted-by":"publisher","first-page":"4206","DOI":"10.1002\/mp.16388","article-title":"Realistic CT data augmentation for accurate deep\u2010learning based segmentation of head and neck tumors in kV images acquired during radiation therapy","volume":"50","author":"Gardner","year":"2023","journal-title":"Med. Phys."},{"key":"pmbadf371bib17","doi-asserted-by":"publisher","first-page":"S39","DOI":"10.1016\/S0167-8140(17)30520-0","article-title":"Motion capture pillow shows potential to replace thermoplastic masks in H&N radiotherapy","volume":"123","author":"Goldsworthy","year":"2017","journal-title":"Radiother. Oncol."},{"key":"pmbadf371bib18","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1137\/S0895479897326432","article-title":"Tikhonov regularization and total least squares","volume":"21","author":"Golub","year":"1999","journal-title":"SIAM J. Matrix Anal. Appl."},{"key":"pmbadf371bib19","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1016\/j.ijrobp.2011.12.004","article-title":"Evaluation of the accuracy of a 3D surface imaging system for patient setup in head and neck cancer radiotherapy","volume":"84","author":"Gopan","year":"2012","journal-title":"Int. J. Radiat. Oncol. Biol. Phys."},{"key":"pmbadf371bib20","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1186\/s13014-023-02390-6","article-title":"Prospects for online adaptive radiation therapy (ART) for head and neck cancer","volume":"19","author":"Guberina","year":"2024","journal-title":"Radiat. Oncol."},{"key":"pmbadf371bib21","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1016\/j.ijrobp.2017.10.016","article-title":"MRI-based assessment of 3D intrafractional motion of head and neck cancer for radiation therapy","volume":"100","author":"Gurney-Champion","year":"2018","journal-title":"Int. J. Radiat. Oncol. Biol. Phys."},{"key":"pmbadf371bib22","doi-asserted-by":"publisher","first-page":"14NT01","DOI":"10.1088\/1361-6560\/ace1d0","article-title":"A patient-specific deep learning framework for 3D motion estimation and volumetric imaging during lung cancer radiotherapy","volume":"68","author":"Hindley","year":"2023","journal-title":"Phys. Med. Biol."},{"key":"pmbadf371bib23","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1115\/1.3662552","article-title":"A new approach to linear filtering and prediction problems","volume":"82","author":"Kalman","year":"1960","journal-title":"J. Fluids Eng. Trans. ASME"},{"key":"pmbadf371bib24","doi-asserted-by":"publisher","DOI":"10.1111\/ecc.13215","article-title":"Exploring head and neck cancer patients\u2019 experiences with radiation therapy immobilisation masks: a qualitative study","volume":"29","author":"Keast","year":"2020","journal-title":"Eur. J. Cancer Care"},{"key":"pmbadf371bib25","doi-asserted-by":"publisher","first-page":"630","DOI":"10.1016\/S0360-3016(02)02756-6","article-title":"Skin toxicity due to intensity-modulated radiotherapy for head-and-neck carcinoma","volume":"53","author":"Lee","year":"2002","journal-title":"Int. J. Radiat. Oncol. Biol. Phys."},{"key":"pmbadf371bib26","doi-asserted-by":"publisher","first-page":"908","DOI":"10.3390\/bioengineering10080908","article-title":"Real-time tracking of laryngeal motion via the surface depth-sensing technique for radiotherapy in laryngeal cancer patients","volume":"10","author":"Lee","year":"2023","journal-title":"Bioengineering"},{"key":"pmbadf371bib27","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/abc303","article-title":"Deep learning-based real-time volumetric imaging for lung stereotactic body radiation therapy: a proof of concept study","volume":"65","author":"Lei","year":"2020","journal-title":"Phys. Med. Biol."},{"key":"pmbadf371bib28","doi-asserted-by":"publisher","first-page":"6009","DOI":"10.1088\/0031-9155\/56\/18\/015","article-title":"On a PCA-based lung motion model","volume":"56","author":"Li","year":"2011","journal-title":"Phys. Med. Biol."},{"key":"pmbadf371bib29","first-page":"1862","volume":"vol Series","author":"Li","year":"2010"},{"key":"pmbadf371bib30","doi-asserted-by":"publisher","first-page":"S280","DOI":"10.1016\/S0167-8140(19)30951-X","article-title":"Can SGRT be used with open masks to set-up HNC patients and reduce intrafractional motion?","volume":"133","author":"Moreira","year":"2019","journal-title":"Radiother. Oncol."},{"key":"pmbadf371bib31","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.radonc.2018.06.032","article-title":"The impact of margin reduction on outcome and toxicity in head and neck cancer patients treated with image-guided volumetric modulated arc therapy (VMAT)","volume":"130","author":"Navran","year":"2019","journal-title":"Radiother. Oncol."},{"key":"pmbadf371bib32","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/ac06e3","article-title":"A real-time IGRT method using a Kalman filter framework to extract 3D positions from 2D projections","volume":"66","author":"Nguyen","year":"2021","journal-title":"Phys. Med. Biol."},{"key":"pmbadf371bib33","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1002\/jmrs.308","article-title":"Exploring the prevalence and experience of mask anxiety for the person with head and neck cancer undergoing radiotherapy","volume":"65","author":"Nixon","year":"2018","journal-title":"J. Med. Radiat. Sci."},{"key":"pmbadf371bib34","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/S1470-2045(10)70290-4","article-title":"Parotid-sparing intensity modulated versus conventional radiotherapy in head and neck cancer (PARSPORT): a phase 3 multicentre randomised controlled trial","volume":"12","author":"Nutting","year":"2011","journal-title":"Lancet Oncol."},{"key":"pmbadf371bib35","doi-asserted-by":"publisher","first-page":"S720","DOI":"10.1016\/j.ijrobp.2012.07.1928","article-title":"The assessment of interfraction and intrafraction setup error with open thermoplastic masks for head-and-neck cancer using CBCT and 3D surface imaging system","volume":"84","author":"Peng","year":"2012","journal-title":"Int. J. Radiat. Oncol. Biol. Phys."},{"key":"pmbadf371bib36","doi-asserted-by":"publisher","first-page":"6649","DOI":"10.1002\/mp.16691","article-title":"Real-time liver motion estimation via deep learning-based angle-agnostic x-ray imaging","volume":"50","author":"Shao","year":"2023","journal-title":"Med. Phys."},{"key":"pmbadf371bib37","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/ada519","article-title":"Real-time CBCT imaging and motion tracking via a single arbitrarily-angled x-ray projection by a joint dynamic reconstruction and motion estimation (DREME) framework","volume":"70","author":"Shao","year":"2025","journal-title":"Phys. Med. Biol."},{"key":"pmbadf371bib38","doi-asserted-by":"publisher","first-page":"425","DOI":"10.1088\/0031-9155\/49\/3\/006","article-title":"Prediction of respiratory tumour motion for real-time image-guided radiotherapy","volume":"49","author":"Sharp","year":"2004","journal-title":"Phys. Med. Biol."},{"key":"pmbadf371bib39","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1016\/j.ijrobp.2004.04.047","article-title":"Randomized trial on two types of thermoplastic masks for patient immobilization during radiation therapy for head-and-neck cancer","volume":"61","author":"Sharp","year":"2005","journal-title":"Int. J. Radiat. Oncol. Biol. Phys."},{"key":"pmbadf371bib40","doi-asserted-by":"publisher","first-page":"880","DOI":"10.1038\/s41551-019-0466-4","article-title":"Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning","volume":"3","author":"Shen","year":"2019","journal-title":"Nat. Biomed. Eng."},{"key":"pmbadf371bib41","doi-asserted-by":"publisher","first-page":"3065","DOI":"10.1088\/1361-6560\/aa6393","article-title":"A Bayesian approach for three-dimensional markerless tumor tracking using kV imaging during lung radiotherapy","volume":"62","author":"Shieh","year":"2017","journal-title":"Phys. Med. Biol."},{"key":"pmbadf371bib42","doi-asserted-by":"publisher","first-page":"4098","DOI":"10.1118\/1.2776236","article-title":"A rigidity penalty term for nonrigid registration","volume":"34","author":"Staring","year":"2007","journal-title":"Med. Phys."},{"key":"pmbadf371bib43","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1145\/504729.504754","article-title":"Probabilistic robotics","volume":"45","author":"Thrun","year":"2002","journal-title":"Commun. ACM"},{"key":"pmbadf371bib44","doi-asserted-by":"publisher","first-page":"S61","DOI":"10.1016\/j.neuroimage.2008.10.040","article-title":"Diffeomorphic demons: efficient non-parametric image registration","volume":"45","author":"Vercauteren","year":"2009","journal-title":"NeuroImage"},{"key":"pmbadf371bib45","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.230024","article-title":"Totalsegmentator: robust segmentation of 104 anatomic structures in CT images","volume":"5","author":"Wasserthal","year":"2023","journal-title":"Radiology"},{"key":"pmbadf371bib46","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2023.109790","article-title":"Cine MRI-based analysis of intrafractional motion in radiation treatment planning of head and neck cancer patients","volume":"186","author":"Weiss","year":"2023","journal-title":"Radiother. Oncol."},{"key":"pmbadf371bib47","doi-asserted-by":"publisher","first-page":"2498","DOI":"10.1118\/1.4918577","article-title":"A method for volumetric imaging in radiotherapy using single x\u2010ray projection","volume":"42","author":"Xu","year":"2015","journal-title":"Med. Phys."},{"key":"pmbadf371bib48","doi-asserted-by":"publisher","first-page":"2007","DOI":"10.1109\/JBHI.2020.3030071","article-title":"Lung respiratory motion estimation based on fast Kalman filtering and 4D CT image registration","volume":"25","author":"Xue","year":"2020","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"pmbadf371bib49","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2024.108390","article-title":"RT-SRTS: angle-agnostic real-time simultaneous 3D reconstruction and tumor segmentation from single x-ray projection","volume":"173","author":"Zhu","year":"2024","journal-title":"Comput. Biol. Med."}],"container-title":["Physics in Medicine &amp; Biology"],"original-title":[],"link":[{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adf371","content-type":"text\/html","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adf371\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adf371","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adf371\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adf371\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adf371\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adf371\/pdf","content-type":"application\/pdf","content-version":"am","intended-application":"similarity-checking"},{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adf371\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T07:38:34Z","timestamp":1755675514000},"score":1,"resource":{"primary":{"URL":"https:\/\/iopscience.iop.org\/article\/10.1088\/1361-6560\/adf371"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,20]]},"references-count":49,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2025,8,20]]},"published-print":{"date-parts":[[2025,9,7]]}},"URL":"https:\/\/doi.org\/10.1088\/1361-6560\/adf371","relation":{},"ISSN":["0031-9155","1361-6560"],"issn-type":[{"value":"0031-9155","type":"print"},{"value":"1361-6560","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,20]]},"assertion":[{"value":"Volumetric imaging during head and neck radiation therapy using a Kalman filter tracking approach","name":"article_title","label":"Article Title"},{"value":"Physics in Medicine & Biology","name":"journal_title","label":"Journal Title"},{"value":"paper","name":"article_type","label":"Article Type"},{"value":"\u00a9 2025 The Author(s). Published on behalf of Institute of Physics and Engineering in Medicine by IOP Publishing Ltd","name":"copyright_information","label":"Copyright Information"},{"value":"2025-04-07","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2025-07-23","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2025-08-20","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}