TY - JOUR
T1 - Nonlinear motion compensation using cubature Kalman filter for in vivo fluorescence microendoscopy in peripheral lung cancer intervention
AU - He, Tiancheng
AU - Xue, Zhong
AU - Alvarado, Miguel Valdivia Y
AU - Wong, Kelvin K.
AU - Xie, Weixin
AU - Wong, Stephen T C
N1 - Funding Information:
This work was supported by the CPRIT grant RP100627 and John S Dunn Research Foundation.
PY - 2013
Y1 - 2013
N2 - Fluorescence microendoscopy can potentially be a powerful modality in minimally invasive percutaneous intervention for cancer diagnosis because it has an exceptional ability to provide micron-scale resolution images in tissues inaccessible to traditional microscopy. After targeting the tumor with guidance by macroscopic images such as computed tomorgraphy or magnetic resonance imaging, fluorescence microendoscopy can help select the biopsy spots or perform an on-site molecular imaging diagnosis. However, one challenge of this technique for percutaneous lung intervention is that the respiratory and hemokinesis motion often renders instability of the sequential image visualization and results in inaccurate quantitative measurement. Motion correction on such serial microscopy image sequences is, therefore, an important post-processing step. We propose a nonlinear motion compensation algorithm using a cubature Kalman filter (NMC-CKF) to correct these periodic spatial and intensity changes, and validate the algorithm using preclinical imaging experiments. The algorithm integrates a longitudinal nonlinear system model using the CKF in the serial image registration algorithm for robust estimation of the longitudinal movements. Experiments were carried out using simulated and real microendoscopy videos captured from the CellVizio 660 system in rabbit VX2 cancer intervention. The results show that the NMC-CKF algorithm yields more robust and accurate alignment results.
AB - Fluorescence microendoscopy can potentially be a powerful modality in minimally invasive percutaneous intervention for cancer diagnosis because it has an exceptional ability to provide micron-scale resolution images in tissues inaccessible to traditional microscopy. After targeting the tumor with guidance by macroscopic images such as computed tomorgraphy or magnetic resonance imaging, fluorescence microendoscopy can help select the biopsy spots or perform an on-site molecular imaging diagnosis. However, one challenge of this technique for percutaneous lung intervention is that the respiratory and hemokinesis motion often renders instability of the sequential image visualization and results in inaccurate quantitative measurement. Motion correction on such serial microscopy image sequences is, therefore, an important post-processing step. We propose a nonlinear motion compensation algorithm using a cubature Kalman filter (NMC-CKF) to correct these periodic spatial and intensity changes, and validate the algorithm using preclinical imaging experiments. The algorithm integrates a longitudinal nonlinear system model using the CKF in the serial image registration algorithm for robust estimation of the longitudinal movements. Experiments were carried out using simulated and real microendoscopy videos captured from the CellVizio 660 system in rabbit VX2 cancer intervention. The results show that the NMC-CKF algorithm yields more robust and accurate alignment results.
KW - Cubature Kalman filter
KW - Fluorescence microendoscopy image sequence
KW - Image-guided intervention
KW - Motion compensation
UR - http://www.scopus.com/inward/record.url?scp=84878220317&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84878220317&partnerID=8YFLogxK
U2 - 10.1117/1.JBO.18.1.016008
DO - 10.1117/1.JBO.18.1.016008
M3 - Article
C2 - 23291716
AN - SCOPUS:84878220317
SN - 1083-3668
VL - 18
JO - Journal of Biomedical Optics
JF - Journal of Biomedical Optics
IS - 1
M1 - 016008
ER -