Abstract
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 language | English (US) |
|---|---|
| Pages (from-to) | 1447-1464 |
| Number of pages | 18 |
| Journal | Physics in Medicine and Biology |
| Volume | 58 |
| Issue number | 5 |
| DOIs | |
| State | Published - Mar 7 2013 |
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ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Radiological and Ultrasound Technology
Cite this
Extracting respiratory signals from thoracic cone beam CT projections. / Yan, Hao; Wang, Xiaoyu; Yin, Wotao; Pan, Tinsu; Ahmad, Moiz; Mou, Xuanqin; Cerviño, Laura; Jia, Xun; Jiang, Steve B.
In: Physics in Medicine and Biology, Vol. 58, No. 5, 07.03.2013, p. 1447-1464.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Extracting respiratory signals from thoracic cone beam CT projections.
AU - Yan, Hao
AU - Wang, Xiaoyu
AU - Yin, Wotao
AU - Pan, Tinsu
AU - Ahmad, Moiz
AU - Mou, Xuanqin
AU - Cerviño, Laura
AU - Jia, Xun
AU - Jiang, Steve B.
PY - 2013/3/7
Y1 - 2013/3/7
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84880931078&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84880931078&partnerID=8YFLogxK
U2 - 10.1088/0031-9155/58/5/1447
DO - 10.1088/0031-9155/58/5/1447
M3 - Article
C2 - 23399757
AN - SCOPUS:84880931078
VL - 58
SP - 1447
EP - 1464
JO - Physics in Medicine and Biology
JF - Physics in Medicine and Biology
SN - 0031-9155
IS - 5
ER -