Paper Info
Title
A novel filter for accurate estimation of fluid pressure and fluid velocity using poroelastography.
Abstract
Fluid pressure and fluid velocity carry important information for cancer diagnosis, prognosis and treatment. Recent work has demonstrated that estimation of these parameters is theoretically possible using ultrasound poroelastography. However, accurate estimation of these parameters requires high quality axial and lateral strain estimates from noisy ultrasound radio frequency (RF) data. In this paper, we propose a filtering technique combining two efficient filters for removal of noise from strain images, i.e., Kalman and nonlinear complex diffusion filters (NCDF). Our proposed filter is based on a novel noise model, which takes into consideration both additive and amplitude modulation noise in the estimated strains. Using finite element and ultrasound simulations, we demonstrate that the proposed filtering technique can significantly improve image quality of lateral strain elastograms along with fluid pressure and velocity elastograms. Technical feasibility of the proposed method on an in vivo set of data is also demonstrated. Our results show that the CNRe of the lateral strain, fluid pressure and fluid velocity as estimated using the proposed technique is higher by at least 10.9%, 51.3% and 334.4% when compared to the results obtained using a Kalman filter only, by at least 8.9%, 27.6% and 219.5% when compared to the results obtained using a NCDF only and by at least 152.3%, 1278% and 742% when compared to the results obtained using a median filter only for all SNRs considered in this study.
Year
DOI
Venue
2018
10.1016/j.compbiomed.2018.08.007
Computers in Biology and Medicine
Keywords
Field
DocType
Ultrasound elastography,Poroelastography,Kalman filter,Diffusion filter,Interstitial fluid pressure,Interstitial fluid velocity
Median filter,Pattern recognition,Computer science,Image quality,Filter (signal processing),Kalman filter,Flow velocity,Amplitude modulation,Diffusion filter,Artificial intelligence,Lateral strain,Acoustics
Journal
Volume
ISSN
Citations 
101
0010-4825
0
PageRank 
References 
Authors
0.34
14
2
Name
Order
Citations
PageRank
Md Tauhidul Islam175.26
Raffaella Righetti221.77