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¹Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA. aiguohan@vt.edu.

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Summary

This summary is machine-generated.

This chapter reviews methods for extracting tissue information from ultrasonic backscatter coefficient (BSC) data. It focuses on model-based approaches, providing a unified framework and discussing model assumptions and limitations.

Keywords:

Backscatter coefficient Form factor Structure function Ultrasonic scattering

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Area of Science:

Medical Imaging
Biophysics
Acoustics

Background:

The ultrasonic backscatter coefficient (BSC) is a key quantitative ultrasound (QUS) parameter.
BSC provides rich information for tissue characterization.
Extracting parameters from BSC is crucial for its full utilization.

Approach:

Reviews two main approaches for parameter extraction from BSC-frequency curves: model-based and model-free.
Focuses on the model-based approach, fitting scattering models to BSC data.
Unifies common BSC models under a theoretical framework, detailing assumptions and conditions.

Key Points:

Discusses underlying assumptions and conditions for various BSC models.
Provides computer code to aid in the application of selected models.
Analyzes the strengths and weaknesses of different BSC models.

Conclusions:

Model-based approaches offer a robust method for tissue characterization using BSC.
Understanding model assumptions is critical for accurate parameter extraction.
This review facilitates the selection and application of appropriate BSC models.