Frequency-Dependent F-Number for CPWC

version 0.1 (311 KB) by mschiffn
Frequency-dependent F-number for coherent plane-wave compounding (CPWC)

15 Downloads

Updated 15 Sep 2021

From GitHub

View License on GitHub

Frequency-Dependent F-Number for Coherent Plane-Wave Compounding

GitHub GitHub repository size GitHub language count GitHub stargazers GitHub forks View on File Exchange Watch on YouTube ko-fi

Simple MATLAB and CUDA implementations of the frequency-dependent F-number [1] for coherent plane-wave compounding.

CIRS040

What is an F-Number?

The F-number significantly reduces image artifacts in all image formation methods using the delay-and-sum (DAS) algorithm, such as

  • coherent plane-wave compounding [2], or
  • synthetic aperture imaging [3].

The F-number, for a uniform linear transducer array, equals the quotient of the focal length and the width of the receive subaperture.

F-number

The usage of a fixed F-number results in a dynamic receive subaperture whose width increases with the focal length.

Established Methods to Compute the F-Number are Contradictory and Yield Frequency-Dependent Results

Established methods to compute the optimal F-number attribute the image artifacts to two different phenomena:

  1. Noise [4], [5], [2]: The directivity of the array elements attenuates the echoes and reduces the signal-to-noise ratio of the recorded signals.

  2. Grating lobes [6], [7]: The width of the receive subaperture determines the grating lobe-to-main lobe ratio.

Both approaches, although yielding similar F-numbers (0.5 <= F <= 2), are mutually contradictory.

Wide array elements, for example, show an increased directivity.
The "Noise" approach suggests the usage of narrow receive subapertures or, equivalently, large F-numbers for such elements to improve the signal-to-noise ratio.
The "Grating lobes" approach, in contrast, permits wide receive subapertures or, equivalently, small F-numbers for such elements because they attenuate the grating lobes.

Both approaches, moreover, yield F-numbers that increase with the frequency.

The DAS algorithm, however, requires a fixed F-number and typically uses the maximum F-number at the upper frequency bound. This F-number satifies the conditions for all lower frequencies but, owing to its suboptimal value, reduces the spatial resolution.

What Does the Proposed F-Number Accomplish?

The proposed F-number not only eliminates image artifacts but also maintains the spatial resolution of the full aperture [1].

This F-number, in particular, prevents the first-order grating lobes from insonifying reflective image structures. The F-number, to this end, uses a closed-form expression, which derives from the far-field sensitivity of the focused receive subaperture, to impose a minimum angular distance on these grating lobes.

How Does the Implementation Work?

A Fourier-domain beamforming algorithm enables the usage of frequency-dependent F-numbers. The algorithm not only varies the width of the receive subaperture with the voxel position but also with the frequency. This additional frequency dependence, in contrast to a fixed F-number, includes additional frequency components that improve both the contrast and the spatial resolution.

Method Width of the receive subaperture Spatial resolution Grating lobe suppression
No F-number always full optimal none
Fixed F-number position-dependent minimal exaggerated
Proposed F-number frequency- and position-dependent almost optimal optimal

Getting Started

  1. Clone the repository or download the release to your local hard drive.
git clone https://github.com/mschiffn/f_number
  1. Add the repository to your MATLAB path using .
addpath( genpath( './f_number' ) )

Folder Structure

The repository has the following structure:

.
├── +auxiliary      # auxiliary functions (e.g., dimension and size check)
├── +cuda           # C++/CUDA implementation and MEX interface
├── +f_numbers      # classes for various types of F-numbers (e.g., constant, directivity-derived, proposed)
├── +normalizations # classes for various types of normalizations (e.g., off, on, window-based)
├── +platforms      # classes for various types of platforms (e.g., CPU, GPU)
├── +windows        # classes for various window functions (e.g., boxcar, Hann, Tukey)
├── das_pw.m        # main function
├── LICENSE         # license file
└── README.md       # this readme

The packages +f_numbers, +normalizations, and +windows contain exemplary class hierarchies to manage various types of F-numbers, normalizations, and window functions.

Image Formation

Use the function das_pw to form images.

In MATLAB type

help das_pw

to obtain an explanation of the input and output arguments.

The typical usage is:

[ image, F_number_values ] = das_pw( positions_x, positions_z, data_RF, f_s, theta_incident, element_width, element_pitch, [ f_lb, f_ub ], c_ref, N_samples_shift, window, F_number, normalization, platform );

The proposed F-number can be instantiated by

chi_lb = 45;  % minimum angular distance of the first-order grating lobes (°)
F_ub = 3;     % maximum permissible F-number
delta = 10;   % safety margin for anti-lobe aliasing (°)
F_number_rx = f_numbers.grating.angle_lb( chi_lb, F_ub, delta );

The directivity-derived F-numbers [4], [5] are

width_over_pitch = 0.918;  % element width-to-element pitch ratio (1)
F_number_rx_1 = f_numbers.directivity.perrot( width_over_pitch );
F_number_rx_2 = f_numbers.directivity.szabo( width_over_pitch );

The standard fixed F-number is

F_number_rx_3 = f_numbers.constant( 3 );

The MEX interface to the C++/CUDA implementation must be compiled:

mexcuda '-L/usr/local/cuda/lib64' -lcudart -lcufft gpu_bf_das_pw_rf.cu

You might have to adapt the library path (here: /usr/local/cuda/lib64) to your system.

References 📓

  1. M. F. Schiffner and G. Schmitz, "Frequency-dependent F-number increases the contrast and the spatial resolution in fast pulse-echo ultrasound imaging," 2021 IEEE Int. Ultrasonics Symp. (IUS), Xi’an, China, Sep. 2021, pp. 1–4. DOI:10.1109/IUS52206.2021.9593488 arXiv Watch on YouTube

  2. G. Montaldo, M. Tanter, J. Bercoff, N. Benech, and M. Fink, “Coherent plane-wave compounding for very high frame rate ultrasonography and transient elastography," IEEE Trans. Ultrason., Ferroelectr., Freq. Control, vol. 56, no. 3, pp. 489–506, Mar. 2009. DOI:10.1109/TUFFC.2009.1067

  3. J. A. Jensen, S. I. Nikolov, K. L. Gammelmark, and M. H. Pedersen, “Synthetic aperture ultrasound imaging,” Ultrasonics, vol. 44, Supplement, e5–e15, Dec. 2006. DOI:10.1016/j.ultras.2006.07.017

  4. V. Perrot, M. Polichetti, F. Varray, and D. Garcia, “So you think you can DAS? A viewpoint on delay-and-sum beamforming,” Ultrasonics, vol. 111, p. 106 309, Mar. 2021. DOI:10.1016/j.ultras.2020.106309

  5. T. L. Szabo, Diagnostic Ultrasound Imaging: Inside Out, 2nd. Elsevier Academic Press, Dec. 2013

  6. B. Delannoy, R. Torguet, C. Bruneel, E. Bridoux, J. M. Rouvaen, and H. Lasota, “Acoustical image reconstruction in parallel-processing analog electronic systems,” J. Appl. Phys., vol. 50, no. 5, pp. 3153–3159, May 1979. DOI:10.1063/1.326397

  7. C. Bruneel, E. Bridoux, B. Delannoy, B. Nongaillard, J. M. Rouvaen, and R. Torguet, “Effect of spatial sampling on an acoustical image reconstruction,” J. Appl. Phys., vol. 49, no. 2, pp. 569–573, Feb. 1978. DOI:10.1063/1.324680

Cite As

mschiffn (2022). Frequency-Dependent F-Number for CPWC (https://github.com/mschiffn/f_number/releases/tag/0.1), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2021a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Tags Add Tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

+f_numbers

+f_numbers/+directivity

+f_numbers/+grating

+windows

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.