Respiratory motion prediction for tumor following radiotherapy by using time-variant seasonal autoregressive techniques

Kei Ichiji, Noriyasu Homma, Masao Sakai, Yoshihiro Takai, Yuichiro Narita, Mokoto Abe, Norihiro Sugita, Makoto Yoshizawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We develop a new prediction method of respiratory motion for accurate dynamic radiotherapy, called tumor following radiotherapy. The method is based on a time-variant seasonal autoregressive (TVSAR) model and extended to further capture time-variant and complex nature of various respiratory patterns. The extended TVSAR can represent not only the conventional quasi-periodical nature, but also the residual components, which cannot be expressed by the quasi-periodical model. Then, the residuals are adaptively predicted by using another autoregressive model. The proposed method was tested on 105 clinical data sets of tumor motion. The average errors were 1.28 ± 0.87 mm and 1.75 ± 1.13 mm for 0.5 s and 1.0 s ahead prediction, respectively. The results demonstrate that the proposed method can outperform the state-of-the-art prediction methods.

Original languageEnglish
Title of host publication2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
Pages6028-6031
Number of pages4
DOIs
Publication statusPublished - 2012 Dec 14
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: 2012 Aug 282012 Sep 1

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
CountryUnited States
CitySan Diego, CA
Period12/8/2812/9/1

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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  • Cite this

    Ichiji, K., Homma, N., Sakai, M., Takai, Y., Narita, Y., Abe, M., Sugita, N., & Yoshizawa, M. (2012). Respiratory motion prediction for tumor following radiotherapy by using time-variant seasonal autoregressive techniques. In 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012 (pp. 6028-6031). [6347368] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/EMBC.2012.6347368