I have recently joined Dr. Dahl's ultrasound imaging lab as a Postdoctoral Research Fellow. My research interests include coherence imaging, synthetic aperture beamforming, and array signal processing in general.
I consider myself a medical ultrasound researcher and engineer. My research interests include synthetic aperture beamforming, coherence imaging, and signal processing in general.
In Part I of this paper, we detected elements blocked by ribs during simulated and in vivo transcostal liver scans, and we turned those elements OFF to compensate for the loss in visibility of liver vasculature. Here, we apply blocked-element detection and adaptive compensation to large synthetic-aperture (SA) data collected through rib samples ex vivo, in order to reduce near-field clutter and to recover lateral resolution. To construct large synthetic transmit and receive apertures, we collected the individual-channel signals from a fully sampled matrix array at multiple and known array locations across the tissue samples. The blocked elements in SAs were detected using the method presented in Part I and retroactively turned OFF, while the subapertures covering intercostal spaces were either compounded, or coherently summed using uniform and adaptive element-weighting schemes. Turning OFF the blocked elements reduced the reverberation clutter by 5 dB on average. Adaptive weighing of the nonblocked elements to rescale the attenuated spatial frequencies reduced sidelobe levels by up to 5 dB for the transcostal acquisitions, and demonstrated a potential to restore lateral resolution to the nonblocked levels. In addition, the arrival-time surfaces were reconstructed to estimate the aberration from intercostal spaces and to offer further means to compensate for the loss of focus quality in transthoracic imaging.
View details for DOI 10.1109/TUFFC.2017.2683562
View details for PubMedID 28328505
During a transcostal ultrasound scan, ribs and other highly attenuating and/or reflective tissue structures can block parts of the array. Blocked elements tend to limit the acoustic window and impede visualization of structures of interest. Here, we demonstrate a method to detect blocked elements and we measure the loss of image quality they introduce in simulation and in vivo. We utilize a fullwave simulation tool and a clinical ultrasound scanner to obtain element signals from fully sampled matrix arrays during simulated and in vivo transcostal liver scans, respectively. The elements that were blocked by a rib showed lower average signal amplitude and lower average nearest-neighbor cross correlation than the elements in the remainder of the 2-D aperture. The growing receive-aperture B-mode images created from the element data indicate that the signals on blocked elements are dominated by noise and that turning them OFF has a potential to improve visibility of liver vasculature. Adding blocked elements to the growing receive apertures for five in vivo transcostal acquisitions resulted in average decrease in vessel contrast and contrast to noise ratio of 19% and 10%, respectively.
View details for DOI 10.1109/TUFFC.2017.2683559
View details for PubMedID 28328504
View details for DOI 10.1117/12.2081434
View details for Web of Science ID 000355579600013
In Part I of the paper, we demonstrated through simulation the potential of volumetric short-lag spatial coherence (SLSC) imaging to improve visualization of hypoechoic targets in three dimensions. Here, we demonstrate the application of volumetric SLSC imaging in phantom and in vivo experiments using a clinical 3-D ultrasound scanner and matrix array. Using a custom single-channel acquisition tool, we collected partially beamformed channel data from the fully sampled matrix array at high speeds and created matched Bmode and SLSC volumes of a vessel phantom and in vivo liver vasculature. 2-D and 3-D images rendered from the SLSC volumes display reduced clutter and improved visibility of the vessels when compared with their B-mode counterparts. We use concurrently acquired color Doppler volumes to confirm the presence of the vessels of interest and to define the regions inside the vessels used in contrast and contrast-to-noise ratio (CNR) calculations. SLSC volumes show higher CNR values than their matched B-mode volumes, while the contrast values appear to be similar between the two imaging methods.
View details for DOI 10.1109/TUFFC.2014.3011
View details for Web of Science ID 000338665500005
View details for PubMedID 24960701
View details for PubMedCentralID PMC4234201
Short-lag spatial coherence (SLSC) imaging is a beamforming technique that has demonstrated improved imaging performance compared with conventional B-mode imaging in previous studies. Thus far, the use of 1-D arrays has limited coherence measurements and SLSC imaging to a single dimension. Here, the SLSC algorithm is extended for use on 2-D matrix array transducers and applied in a simulation study examining imaging performance as a function of subaperture configuration and of incoherent channel noise. SLSC images generated with a 2-D array yielded superior contrast-to-noise ratio (CNR) and texture SNR measurements over SLSC images made on a corresponding 1-D array and over B-mode imaging. SLSC images generated with square subapertures were found to be superior to SLSC images generated with subapertures of equal surface area that spanned the whole array in one dimension. Subaperture beamforming was found to have little effect on SLSC imaging performance for subapertures up to 8 x 8 elements in size on a 64 × 64 element transducer. Additionally, the use of 8 x 8, 4 x 4, and 2 x 2 element subapertures provided 8, 4, and 2 times improvement in channel SNR along with 2640-, 328-, and 25-fold reduction in computation time, respectively. These results indicate that volumetric SLSC imaging is readily applicable to existing 2-D arrays that employ subaperture beamforming.
View details for DOI 10.1109/TUFFC.2014.3010
View details for Web of Science ID 000338665500004
View details for PubMedID 24960700
View details for PubMedCentralID PMC4235772
In vivo ultrasonic imaging with transducer arrays suffers from image degradation resulting from beamforming limitations, including diffraction-limited beamforming and beamforming degradation caused by tissue inhomogeneity. Additionally, based on recent studies, multipath scattering also causes significant image degradation. To reduce degradation from both sources, we propose a model-based signal decomposition scheme. The proposed algorithm identifies spatial frequency signatures to decompose received wavefronts into their most significant scattering sources. Scattering sources originating from a region of interest are used to reconstruct decluttered wavefronts, which are beamformed into decluttered RF scan lines or A-lines. To test the algorithm, ultrasound system channel data were acquired during liver scans from 8 patients. Multiple data sets were acquired from each patient, with 55 total data sets, 43 of which had identifiable hypoechoic regions on normal B-mode images. The data sets with identifiable hypoechoic regions were analyzed. The results show the decluttered B-mode images have an average improvement in contrast over normal images of 7.3 ± 4.6 dB. The contrast-to-noise ratio (CNR) changed little on average between normal and decluttered Bmode, -0.4 ± 5.9 dB. The in vivo speckle SNR decreased; the change was -0.65 ± 0.28. Phantom speckle SNR also decreased, but only by -0.40 ± 0.03.
View details for DOI 10.1109/TUFFC.2014.2928
View details for Web of Science ID 000332609400006
View details for PubMedID 24569248
View details for DOI 10.1109/ULTSYM.2014.0421
View details for Web of Science ID 000352792500419
We present the results of a patient study conducted to assess the performance of two novel imaging methods, namely short-lag spatial coherence (SLSC) and harmonic spatial coherence imaging (HSCI), in an in vivo liver environment. Similar in appearance to the B-mode images, SLSC and HSCI images are based solely on the spatial coherence of fundamental and harmonic echo data, respectively, and do not depend on the echo magnitude. SLSC and HSCI suppress incoherent echo signals and thus tend to reduce clutter. The SLSC and HSCI images of 17 patients demonstrated sharper delineation of blood vessel walls, suppressed clutter inside the vessel lumen, and showed reduced speckle in surrounding tissue compared to matched B-modes. Target contrast and contrast-to-noise ratio (CNR) show statistically significant improvements between fundamental B-mode and SLSC imaging and between harmonic B-mode and HSCI imaging (in all cases p < 0.001). The magnitude of improvement in contrast and CNR increases as the overall quality of B-mode images decreases. Poor-quality fundamental B-mode images (where image quality classification is based on both contrast and CNR) exhibit the highest improvements in both contrast and CNR (288% improvement in contrast and 533% improvement in CNR).
View details for DOI 10.1016/j.ultrasmedbio.2012.09.022
View details for Web of Science ID 000314872200015
View details for PubMedID 23347642
View details for PubMedCentralID PMC3638043
View details for DOI 10.1109/ULTSYM.2013.0331
View details for Web of Science ID 000336665300328
We introduce a harmonic version of the short-lag spatial coherence (SLSC) imaging technique, called harmonic spatial coherence imaging (HSCI). The method is based on the coherence of the second-harmonic backscatter. Because the same signals that are used to construct harmonic B-mode images are also used to construct HSCI images, the benefits obtained with harmonic imaging are also obtained with HSCI. Harmonic imaging has been the primary tool for suppressing clutter in diagnostic ultrasound imaging, however secondharmonic echoes are not necessarily immune to the effects of clutter. HSCI and SLSC imaging are less sensitive to clutter because clutter has low spatial coherence. HSCI shows favorable imaging characteristics such as improved contrast-to-noise ratio (CNR), improved speckle SNR, and better delineation of borders and other structures compared with fundamental and harmonic B-mode imaging. CNRs of up to 1.9 were obtained from in vivo imaging of human cardiac tissue with HSCI, compared with 0.6, 0.9, and 1.5 in fundamental B-mode, harmonic B-mode, and SLSC imaging, respectively. In vivo experiments in human liver tissue demonstrated SNRs of up to 3.4 for HSCI compared with 1.9 for harmonic B-mode. Nonlinear simulations of a heart chamber model were consistent with the in vivo experiments.
View details for DOI 10.1109/TUFFC.2012.2243
View details for Web of Science ID 000303405500004
View details for PubMedID 22547276
View details for PubMedCentralID PMC3342045
We report the development and evaluation of a simple compact probe that incorporates multiple beveled fibers for depth sensitive detection of spectroscopic signals in vivo. We evaluated three probes with bevel angles 35, 40, and 45 degrees for their collection efficiency and depth resolution using a thin highly scattering white substrate and found that a 40 degree bevel provides the best characteristics for depth-resolved spectroscopy. The depth sensitivity of the probe with 40 degree beveled fibers was then evaluated using multilayer phantoms with scattering properties mimicking precancerous tissue and in vivo on normal human oral mucosa. The results demonstrate that the use of multiple beveled fibers has the capability to simultaneously collect scattering spectra from a range of depths within epithelial tissue that has the potential to provide further significant improvement of detection and monitorin of epithelial precancers.
View details for DOI 10.1364/OE.17.002780
View details for Web of Science ID 000263432500073
View details for PubMedID 19219183
