Paper Info
Title
Compensated Row-Column Ultrasound Imaging Systems With Data-Driven Point Spread Function Learning
Abstract
Ultrasound imaging systems are invaluable tools used in applications ranging from medical diagnostics to non-destructive testing. The concept of row-column imaging using row-column-addressed arrays has received a lot of attention recently for 3-D ultrasound imaging. However, it suffers from a few intrinsic limitations: data sparsity, speckle noise, and a spatially varying point spread function. These limitations cannot be addressed by transducer design alone. In this research, we propose PL-UIS, a compensated ultrasound imaging system that combines physical modeling with data-driven spatially varying point spread function learning within a random field framework to address the limitations of row-column ultrasound imaging. Experimental results using the proposed ultrasound imaging system show the effectiveness of our proposed PL-UIS system compared to state-of-the-art compensated ultrasound imaging systems.
Year
DOI
Venue
2019
10.1007/978-3-030-27272-2_38
IMAGE ANALYSIS AND RECOGNITION (ICIAR 2019), PT II
Keywords
DocType
Volume
Ultrasound imaging, Non-stationary point spread function, Conditional random fields, Point spread function learning
Conference
11663
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Ibrahim Ben Daya102.70
John T W Yeow2106.58
Alexander Wong335169.61