Journal article
Statistics of Boundaries in Ultrasonic B-Scan Images
Ultrasound in medicine & biology, v 41(1), pp 268-280
Jan 2015
PMID: 25438836
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The existence of edges and boundaries in regions of interest (ROIs) in B-scan images alters the statistics of the backscattered echo from the ROI. Boundaries are the result of at least two different types of scattering scenarios in tissue, and the Nakagami model, which is being used extensively in ultrasound, is unlikely to fit the statistics of the backscattered echo under these conditions. Furthermore, there are very few other statistical models exist that describe the statistics of the backscattered echo from regions containing boundaries. In this work, the gamma mixture density and the recently proposed McKay density are explored as two viable models to fill this void. Justifications of these models are presented along with methods for estimating their parameters. Random number simulations and studies on tissue-mimicking phantoms indicate that the McKay and gamma mixture densities are the best for the modeling of the backscattered echo intensity when boundaries are present in the regions of interest.
Metrics
Details
- Title
- Statistics of Boundaries in Ultrasonic B-Scan Images
- Creators
- P. Mohana Shankar - Department of Electrical & Computer Engineering, Drexel University, Philadelphia, Pennsylvania, USA
- Publication Details
- Ultrasound in medicine & biology, v 41(1), pp 268-280
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000347898500027
- Scopus ID
- 2-s2.0-84919682933
- Other Identifier
- 991014878011804721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Acoustics
- Radiology, Nuclear Medicine & Medical Imaging