A comparative study of a novel AE-nLMS filter and two traditional filters in predicting respiration induced motion of the tumor

Ke Huang, Ivan Buzurovic, Yan Yu, Tarun K. Podder

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

6 Scopus citations

Abstract

Prediction of tumor motion is one of the important steps in active tracking of tumor and dynamic delivery of radiation dose to tumor. In this paper, we have presented a novel adaptive acceleration-enhanced normalized least mean squares (AE-nLMS) prediction filter based on the adaptive normalized least mean squares (nLMS) filter with predicted acceleration and ratio between the real and predicted acceleration taken into account. We have compared the performances of nLMS, artificial neural network (ANN), and AE-nLMS filter for predicting the respiration motion during normal and irregular respiration. The results revealed that the ANN filter has the best performance in the prediction of normal respiration motion, whereas the AE-nLMS filter outperformed other filters in the prediction of irregular respiration motion.

Original languageEnglish (US)
Title of host publication10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010
Pages281-282
Number of pages2
DOIs
StatePublished - Sep 6 2010
Event10th IEEE International Conference on Bioinformatics and Bioengineering, BIBE-2010 - Philadelphia, PA, United States
Duration: May 31 2010Jun 3 2010

Publication series

Name10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010

Other

Other10th IEEE International Conference on Bioinformatics and Bioengineering, BIBE-2010
CountryUnited States
CityPhiladelphia, PA
Period5/31/106/3/10

Keywords

  • Acceleration-enhanced filter
  • Adaptive filter
  • Motion tracking
  • Prediction
  • Respiration
  • Tumor motion

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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  • Cite this

    Huang, K., Buzurovic, I., Yu, Y., & Podder, T. K. (2010). A comparative study of a novel AE-nLMS filter and two traditional filters in predicting respiration induced motion of the tumor. In 10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010 (pp. 281-282). [5521676] (10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010). https://doi.org/10.1109/BIBE.2010.53