Biomedical subjects

Jeremy J Dahl

Publications and source records attributed to Jeremy J Dahl.

9 recordsLinked to original sources

PubMed2007

An ultrasound research interface for a clinical system.

Under a contract with the National Cancer Institute, we have developed a research interface to an ultrasound system. This ultrasound research interface (URI) is an optional feature providing several basic capabilities not normally available on a clinical scanner. The URI can store high-quality beamformed radio-frequency data to file for off-line processing. Also, through an integrated user interface, the user is provided additional control over the B-mode receive aperture and color flow ensemble size. A third major capability is the ability to record and playback macro files. In this paper, we describe the URI and illustrate its use on three research examples: elastography, computed tomography, and spatial compounding.

Biomedical Research↗

PubMed2006

An ultrasound research interface for a clinical system.

Biomedical Research↗

PubMed2006

Adaptive imaging on a diagnostic ultrasound scanner at quasi real-time rates.

Constructing an ultrasonic imaging system capable of compensating for phase errors in real-time is a significant challenge in adaptive imaging. We present a versatile adaptive imaging system capable of updating arrival time profiles at frame rates of approximately 2 frames per second (fps) with 1-D arrays and up to 0.81 fps for 1.75-D arrays, depending on the desired near-field phase correction algorithm. A novel feature included in this system is the ability to update the aberration profile at multiple beam locations for 1-D arrays. The features of this real-time adaptive imaging system are illustrated in tissue-mimicking phantoms with physical near-field phase screens and evaluated in clinical breast tissue with a 1.75-D array. The contrast-to-noise ratio (CNR) of anechoic cysts was shown to improve dramatically in the tissue-mimicking phantoms. In breast tissue, the width of point-like targets showed significant improvement: a reduction of 26.2% on average. Brightness of these targets, however, marginally decreased by 3.9%. For larger structures such as cysts, little improvement in features and CNR were observed, which is likely a result of the system assuming an infinite isoplanatic patch size for the 1.75-D arrays. The necessary requirements for constructing a real-time adaptive imaging system are also discussed.

Computer Systems↗

PubMed2006

Rapid tracking of small displacements with ultrasound.

Time-delay estimators, such as normalized cross correlation and phase-shift estimation, form the computational basis for elastography, blood flow measurements, and acoustic radiation force impulse (ARFI) imaging. This paper examines the performance of these algorithms for small displacements (less than half the ultrasound pulse wavelength). The effects of noise, bandwidth, stationary echoes, kernel size, downsampling, interpolation, and quadrature demodulation on the accuracy of the time delay estimates are measured in terms of bias and jitter. Particular attention is given to the accuracy and resolution of the displacement measurements and to the computational efficiency of the algorithms. In most cases, Loupas' two-dimensional (2-D) autocorrelator performs as well as the gold standard, normalized cross correlation. However, Loupas' algorithm's calculation time is significantly faster, and it is particularly suited to operate on the signal data format most commonly used in ultrasound scanners. These results are used to implement a real-time ARFI imaging system using a commercial ultrasound scanner and a computer cluster. Images processed with the algorithms are examined in an ex vivo liver ablation study.

Algorithms↗

PubMed2006

Phase-aberration correction with a 3-D ultrasound scanner: feasibility study.

We tested the feasibility of using adaptive imaging, namely phase-aberration correction, with two-dimensional (2-D) arrays and real-time, 3-D ultrasound. Because of the high spatial frequency content of aberrators, 2-D arrays, which generally have smaller pitch and thus higher spatial sampling frequency, and 3-D imaging show potential to improve the performance of adaptive imaging. Phase-correction algorithms improve image quality by compensating for tissue-induced errors in beamforming. Using the illustrative example of transcranial ultrasound, we have evaluated our ability to perform adaptive imaging with a real-time, 3-D scanner. We have used a polymer casting of a human temporal bone, root-mean-square (RMS) phase variation of 45.0 ns, full-width-half-maximum (FWHM) correlation length of 3.35 mm, and an electronic aberrator, 100 ns RMS, 3.76 mm correlation, with tissue phantoms as illustrative examples of near-field, phase-screen aberrators. Using the multilag, least-squares, cross-correlation method, we have shown the ability of 3-D adaptive imaging to increase anechoic cyst identification, image brightness, contrast-to-speckle ratio (CSR), and, in 3-D color Doppler experiments, the ability to visualize flow. For a physical aberrator skull casting we saw CSR increase by 13% from 1.01 to 1.14, while the number of detectable cysts increased from 4.3 to 7.7.

Algorithms↗

PubMed2005

Adaptive imaging and spatial compounding in the presence of aberration.

Spatial compounding reduces speckle and increases image contrast by incoherently averaging images acquired at different viewing angles. Adaptive imaging improves contrast and resolution by compensating for tissue-induced phase errors. Aberrator strength and spatial frequency content markedly impact the desirable operating characteristics and performance of these methods for improving image quality. Adaptive imaging, receive-spatial compounding, and a combination of these two methods are presented in contrast and resolution tasks under various aberration characteristics. All three imaging methods yield increases in the contrast-to-noise ratio (CNR) of anechoic cysts; however, the improvements vary depending on the properties of the aberrating layer. Phase correction restores image spatial frequencies, and the addition of compounding opposes the restoration of image spatial frequencies. Lesion signal-to-noise ratio (SNR), an image quality metric for predicting lesion detectability, shows that combining spatial compounding with phase correction yields the maximum detectability when the aberrator strength or spatial frequency content is high. Examples of these modes are presented in thyroid tissue.

Algorithms↗

PubMed2005

Spatial and temporal aberrator stability for real-time adaptive imaging.

Reported real-time adaptive imaging systems use near-field phase correction techniques, which are desired because of their simple implementation and their compatibility with current system architectures. Aberrator stability is important to adaptive imaging because it defines the spatial and temporal limits for which the near-field phase estimates are valid. Spatial aberrator stability determines the required spatial sampling of the aberrator, and temporal aberrator stability determines the length of time for which the aberration profile can be used. In this study, the spatial and temporal stability of clinically measured aberrations is reported for breast, liver, and thyroid tissue. Cross correlations between aberration estimates revealed aberrators to have azimuthal isoplanatic patch sizes of 0.44, 0.28, and 0.20 mm for breast, liver, and thyroid tissue, respectively, at 80% correlation. Axial isoplanatic patch sizes were 1.26, 0.76, and 1.80 mm for the same tissue, respectively, at 80% correlation. Temporal stability at 80% correlation was determined to be greater than 1.5 seconds for breast and thyroid tissue, and 0.65 seconds for the liver. The effects of noise, motion, and target nonuniformity on aberrator stability are characterized by simulations and experiments in tissue mimicking phantoms.

Algorithms↗

PubMed2004

Clinical evaluation of combined spatial compounding and adaptive imaging in breast tissue.

When spatial compounding is applied to targets with significant acoustic velocity inhomogeneities, the correlation between speckle patterns of the images to be averaged decreases, thereby increasing the speckle reduction nominally obtained. Phase correction applied to these targets improves the coherence of the wavefield and restores image spatial frequencies. Combining these two modes can be used to effectively increase the contrast-to-noise ratio (CNR) of imaging targets and improve the general image quality of these targets over spatial compounding alone. This paper presents a clinical evaluation of combined spatial compounding and adaptive imaging in breast tissue and compares this combined technique to conventional imaging and to adaptive imaging and spatial compounding operating independently. Experiments were performed on a 1.75-D, 8 x 96 array attached to a commercially-available scanner. Cysts, microcalcifications and other breast structures were targeted in order to assess the impact of the combined mode on CNR, target width, target brightness and target peak-to-background ratio (PBR). In general, phase correction improved cyst CNR by 7.7%, decreased target width by 18.7%, increased target brightness by 30.1% and increased PBR by 17.9%. Compounding alone, using three overlapping 9.71 mm subapertures, increased cyst CNR by 24.6%, but increased target width by 25.4% and decreased PBR by 13.2%. Combining both modes, however, increased cyst CNR by 32.6%, inappreciably increased target width by 1.1% and marginally decreased PBR by 2.8%. The increase in target brightness with this combined mode was 20.0%

Adult↗

PubMed2003

Synthetic elevation beamforming and image acquisition capabilities using an 8 x 128 1.75D array.

Ultrasound imaging can be improved with higher order arrays through elevation dynamic focusing in future, higher channel count systems. However, modifications to current system hardware could yield increased imaging depth-of-field with 1.75D arrays (arrays with individually addressable elements, several rows in elevation) through the use of synthetic elevation imaging. We describe synthetic elevation beamforming methods and its implementation with our 8 x 128, 1.75D array (Tetrad Co., Englewood, CO). This array has been successfully interfaced with a Siemens Elegra scanner for summed RF and single channel RF data acquisition. Individual rows of the 8 x 128 array can be controlled, allowing for different aperture configurations on transmit and receive beamforming. Advantages of using this array include finer elevation sampling, a larger array footprint for aberration measurements, and elevation focusing. We discuss system tradeoffs that occur in implementing synthetic receive and synthetic transmit/receive elevation focusing and show significant image quality improvements in simulation and phantom data results.

Algorithms↗