TY - GEN
T1 - Parametric perfusion imaging using contrast enhanced ultrasound with bolus administration of contrast agents
AU - Gu, Xiaolin
AU - Zong, Yujin
AU - Zhong, Hui
AU - Wan, Mingxi
PY - 2012
Y1 - 2012
N2 - Pixel-by-pixel parametric perfusion imaging can show the space distribution of blood flow rate and blood volume that is valuable for clinical diagnosis and treatment assessment. In this study, the feasibility of Nakagami imaging for suppressing attenuation effects was investigated. In order to avoid recirculation, a minimum-based method in determining curve interval for fitting was proposed and compared with threshold-based method. Three bolus kinetics models including gamma variate model, lognormal model and local density random walk model were used for curve fitting and compared. Parametric perfusion images were formed and discussed. Simulation and in vivo experiment were conducted for validation. The results show that Nakagami imaging is insensitive to attenuation effects. Minimum-based method is more efficient and robust in avoiding recirculation. Lognormal model provides optimal performance on curve fitting.
AB - Pixel-by-pixel parametric perfusion imaging can show the space distribution of blood flow rate and blood volume that is valuable for clinical diagnosis and treatment assessment. In this study, the feasibility of Nakagami imaging for suppressing attenuation effects was investigated. In order to avoid recirculation, a minimum-based method in determining curve interval for fitting was proposed and compared with threshold-based method. Three bolus kinetics models including gamma variate model, lognormal model and local density random walk model were used for curve fitting and compared. Parametric perfusion images were formed and discussed. Simulation and in vivo experiment were conducted for validation. The results show that Nakagami imaging is insensitive to attenuation effects. Minimum-based method is more efficient and robust in avoiding recirculation. Lognormal model provides optimal performance on curve fitting.
UR - https://www.scopus.com/pages/publications/84864267645
U2 - 10.1109/BHI.2012.6211670
DO - 10.1109/BHI.2012.6211670
M3 - 会议稿件
AN - SCOPUS:84864267645
SN - 9781457721779
T3 - Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012
SP - 663
EP - 666
BT - Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics
T2 - IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health Engineering
Y2 - 2 January 2012 through 7 January 2012
ER -