Journal article
Non-Rayleigh statistics of ultrasonic backscattered signals
IEEE transactions on ultrasonics, ferroelectrics, and frequency control, v 41(6), pp 845-852
01 Jan 1994
PMID: 18263274
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The statistics of the envelope of the backscattered signal from tissues have been known to vary from the well-known Rayleigh model. The K-distribution is used to model this non-Rayleigh behavior, since the generalized K-distribution encompasses a wide range of distributions like Rayleigh, Lognormal, and Rician. Computer simulations were conducted using a simple one-dimensional discrete scattering model to investigate the properties of the echo envelope. Significant departures from Rayleigh statistics were seen as the scattering cross sections of the scatterers became random. The validity of this model was also tested using data from tissue mimicking phantoms. Results indicate that the density function of the envelope can be modeled by the K-distribution and the parameters of the K-distribution can provide information on the nature of the scattering region in terms of the number as well as the scattering cross sections of the scatterers.
Metrics
Details
- Title
- Non-Rayleigh statistics of ultrasonic backscattered signals
- Creators
- VManoj Narayanan - Drexel UniversityP ShankarJohn ReidP Mohana Shankar - Electrical and Computer Engineering
- Publication Details
- IEEE transactions on ultrasonics, ferroelectrics, and frequency control, v 41(6), pp 845-852
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering; School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:A1994PP10600007
- Scopus ID
- 2-s2.0-0028543046
- Other Identifier
- 991019183938004721
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
- Engineering, Electrical & Electronic