{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/predicting-respiratory-motion-for-real-time","title":"Predicting respiratory motion for real-time tumour tracking in radiotherapy","arxiv_id":"1508.00749","date":"2015-08-04","proceeding":null,"authors":["Tomas Krilavicius","Indre Zliobaite","Henrikas Simonavicius","Laimonas Jarusevicius"],"abstract":"Purpose. Radiation therapy is a local treatment aimed at cells in and around\na tumor. The goal of this study is to develop an algorithmic solution for\npredicting the position of a target in 3D in real time, aiming for the short\nfixed calibration time for each patient at the beginning of the procedure.\nAccurate predictions of lung tumor motion are expected to improve the precision\nof radiation treatment by controlling the position of a couch or a beam in\norder to compensate for respiratory motion during radiation treatment.\n  Methods. For developing the algorithmic solution, data mining techniques are\nused. A model form from the family of exponential smoothing is assumed, and the\nmodel parameters are fitted by minimizing the absolute disposition error, and\nthe fluctuations of the prediction signal (jitter). The predictive performance\nis evaluated retrospectively on clinical datasets capturing different behavior\n(being quiet, talking, laughing), and validated in real-time on a prototype\nsystem with respiratory motion imitation.\n  Results. An algorithmic solution for respiratory motion prediction (called\nExSmi) is designed. ExSmi achieves good accuracy of prediction (error $4-9$\nmm/s) with acceptable jitter values (5-7 mm/s), as tested on out-of-sample\ndata. The datasets, the code for algorithms and the experiments are openly\navailable for research purposes on a dedicated website.\n  Conclusions. The developed algorithmic solution performs well to be\nprototyped and deployed in applications of radiotherapy.","url_abs":"http://arxiv.org/abs/1508.00749v1","url_pdf":"http://arxiv.org/pdf/1508.00749v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":null,"task_name":"Position"},{"task_slug":"motion-prediction","task_name":"motion prediction"}],"methods":[],"datasets_introduced":[{"slug":"extmarker","name":"ExtMarker","full_name":"3D motion of chest external markers"}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}