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.
Duke Scholars
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Related Subject Headings
- Ultrasonography
- Sensitivity and Specificity
- Reproducibility of Results
- Phantoms, Imaging
- Information Storage and Retrieval
- Imaging, Three-Dimensional
- Image Interpretation, Computer-Assisted
- Image Enhancement
- Humans
- Feasibility Studies
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Ultrasonography
- Sensitivity and Specificity
- Reproducibility of Results
- Phantoms, Imaging
- Information Storage and Retrieval
- Imaging, Three-Dimensional
- Image Interpretation, Computer-Assisted
- Image Enhancement
- Humans
- Feasibility Studies