Extracting respiratory signals from thoracic cone beam CT projections.

Hao Yan, Xiaoyu Wang, Wotao Yin, Tinsu Pan, Moiz Ahmad, Xuanqin Mou, Laura Cerviño, Xun Jia, Steve B. Jiang

Research output: Contribution to journalArticlepeer-review

40 Scopus citations


The patient respiratory signal associated with the cone beam CT (CBCT) projections is important for lung cancer radiotherapy. In contrast to monitoring an external surrogate of respiration, such a signal can be extracted directly from the CBCT projections. In this paper, we propose a novel local principal component analysis (LPCA) method to extract the respiratory signal by distinguishing the respiration motion-induced content change from the gantry rotation-induced content change in the CBCT projections. The LPCA method is evaluated by comparing with three state-of-the-art projection-based methods, namely the Amsterdam Shroud method, the intensity analysis method and the Fourier-transform-based phase analysis method. The clinical CBCT projection data of eight patients, acquired under various clinical scenarios, were used to investigate the performance of each method. We found that the proposed LPCA method has demonstrated the best overall performance for cases tested and thus is a promising technique for extracting a respiratory signal. We also identified the applicability of each existing method.

Original languageEnglish (US)
Pages (from-to)1447-1464
Number of pages18
JournalUnknown Journal
Issue number5
StatePublished - Mar 7 2013

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging


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