My research interests are focused on the development and clinical translation of new ultrasound imaging techniques to improve the quality and diagnostic value of ultrasound imaging. My interests are in clinical translation of ultrasound molecular imaging for early cancer detection, improving image quality in difficult-to-image patients, and to reduce noise artifacts in ultrasound images. In my research, I have refined adaptive beamforming methods such as coherence-based imaging, helped to pioneer the use of deep learning tools on raw ultrasound data to produce more accurate B-mode images and more sensitive ultrasound molecular images, and developed GPU-based software beamforming tools to deploy these methods in real-time on experimental and clinical imaging systems.


All Publications

  • Acoustically Driven Microbubbles Enable Targeted Delivery of microRNA-Loaded Nanoparticles to Spontaneous Hepatocellular Neoplasia in Canines ADVANCED THERAPEUTICS Kumar, S., Telichko, A. V., Wang, H., Hyun, D., Johnson, E. G., Kent, M. S., Rebhun, R. B., Dahl, J. J., Culp, W. N., Paulmurugan, R. 2020
  • Extending Retrospective Encoding for Robust Recovery of the Multistatic Data Set IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL Ali, R., Herickhoff, C. D., Hyun, D., Dahl, J. J., Bottenus, N. 2020; 67 (5): 943–56


    Robust recovery of multistatic synthetic aperture data from conventional ultrasound sequences can enable complete transmit-and-receive focusing at all points in the field of view without the drawbacks of virtual-source synthetic aperture and further enables more advanced imaging applications, such as backscatter coherence, sound speed estimation, and phase aberration correction. Recovery of the multistatic data set has previously been demonstrated on a steered transmit sequence for phased arrays using an adjoint-based method. We introduce two methods to improve the accuracy of the multistatic data set. We first modify the original technique used for steered transmit sequences by applying a ramp filter to compensate for the nonuniform frequency scaling introduced by the adjoint-based method. Then, we present a regularized inversion technique that allows additional aperture specification and is intended to work for both steered transmit and walking aperture sequences. The ramp-filtered adjoint and regularized inversion techniques, respectively, improve the correlation of the recovered signal with the ground truth from 0.9404 to 0.9774 and 0.9894 in steered transmit sequences and 0.4610 to 0.4733 and 0.9936 in walking aperture sequences.

    View details for DOI 10.1109/TUFFC.2019.2961875

    View details for Web of Science ID 000531321300006

    View details for PubMedID 31870983

  • Effects of motion on correlations of pulse-echo ultrasound signals: Applications in delay estimation and aperture coherence JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA Hyun, D., Dahl, J. J. 2020; 147 (3): 1323–32

    View details for DOI 10.1121/10.0000809

    View details for Web of Science ID 000519550900001

  • Nondestructive Detection of Targeted Microbubbles Using Dual-Mode Data and Deep Learning for Real-Time Ultrasound Molecular Imaging. IEEE transactions on medical imaging Hyun, D., Abou-Elkacem, L., Bam, R., Brickson, L. L., Herickhoff, C. D., Dahl, J. J. 2020


    Ultrasound molecular imaging (UMI) is enabled by targeted microbubbles (MBs), which are highly reflective ultrasound contrast agents that bind to specific biomarkers. Distinguishing between adherent MBs and background signals can be challenging in vivo. The preferred preclinical technique is differential targeted enhancement (DTE), wherein a strong acoustic pulse is used to destroy MBs to verify their locations. However, DTE intrinsically cannot be used for real-time imaging and may cause undesirable bioeffects. In this work, we propose a simple 4-layer convolutional neural network to nondestructively detect adherent MB signatures. We investigated several types of input data to the network: "anatomy-mode" (fundamental frequency)", contrast-mode" (pulse-inversion harmonic frequency), or both, i.e.", dual-mode", using IQ channel signals, the channel sum, or the channel sum magnitude. Training and evaluation were performed on in vivo mouse tumor data and microvessel phantoms. The dual-mode channel signals yielded optimal performance, achieving a soft Dice coefficient of 0.45 and AUC of 0.91 in two test images. In a volumetric acquisition, the network best detected a breast cancer tumor, resulting in a generalized contrast-to-noise ratio (GCNR) of 0.93 and Kolmogorov-Smirnov statistic (KSS) of 0.86, outperforming both regular contrast mode imaging (GCNR=0.76, KSS=0.53) and DTE imaging (GCNR=0.81, KSS=0.62). Further development of the methodology is necessary to distinguish free from adherent MBs. These results demonstrate that neural networks can be trained to detect targeted MBs with DTE-like quality using nondestructive dual-mode data, and can be used to facilitate the safe and real-time translation of UMI to clinical applications.

    View details for DOI 10.1109/TMI.2020.2986762

    View details for PubMedID 32286963

  • Short-Lag Spatial Coherence Imaging in 1.5-D and 1.75-D Arrays: Elevation Performance and Array Design Considerations IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL Morgan, M. R., Hyun, D., Trahey, G. E. 2019; 66 (6): 1047–56


    Short-lag spatial coherence (SLSC) imaging has demonstrated improved performance over conventional B-Mode ultrasound imaging. Previous work has evaluated the performance of SLSC using 2-D matrix arrays in simulation and in vivo studies across various levels of subaperture beamforming, demonstrating improved contrast-to-noise ratio (CNR) and speckle signal-to-noise ratio (SNR) over 1-D arrays. This work explores the application of SLSC imaging in 1.5-D and 1.75-D arrays to quantify the impacts of elevation element count, mirroring, and Fresnel element spacing on SLSC image quality. Through simulation and in vivo studies, increased elevation element count was shown to improve CNR and speckle SNR relative to 1-D SLSC and B-Mode images. Elevation mirroring (1.5-D) was shown to force the inclusion of long lags into the SLSC calculation, introducing additional decorrelation and reducing image quality relative to 1.75-D arrays with individually-connected elements. These results demonstrate the effectiveness of SLSC imaging in 1.5-D and 1.75-D arrays.

    View details for DOI 10.1109/TUFFC.2019.2906553

    View details for Web of Science ID 000470985900004

    View details for PubMedID 30908212

  • Beamforming and Speckle Reduction Using Neural Networks. IEEE transactions on ultrasonics, ferroelectrics, and frequency control Hyun, D., Brickson, L. L., Looby, K. T., Dahl, J. J. 2019; 66 (5): 898–910


    With traditional beamforming methods, ultrasound B-mode images contain speckle noise caused by the random interference of subresolution scatterers. In this paper, we present a framework for using neural networks to beamform ultrasound channel signals into speckle-reduced B-mode images. We introduce log-domain normalization-independent loss functions that are appropriate for ultrasound imaging. A fully convolutional neural network was trained with the simulated channel signals that were coregistered spatially to ground-truth maps of echogenicity. Networks were designed to accept 16 beamformed subaperture radio frequency (RF) signals. Training performance was compared as a function of training objective, network depth, and network width. The networks were then evaluated on the simulation, phantom, and in vivo data and compared against the existing speckle reduction techniques. The most effective configuration was found to be the deepest (16 layer) and widest (32 filter) networks, trained to minimize a normalization-independent mixture of the l1 and multiscale structural similarity (MS-SSIM) losses. The neural network significantly outperformed delay-and-sum (DAS) and receive-only spatial compounding in speckle reduction while preserving resolution and exhibited improved detail preservation over a nonlocal means method. This work demonstrates that ultrasound B-mode image reconstruction using machine-learned neural networks is feasible and establishes that networks trained solely in silico can be generalized to real-world imaging in vivo to produce images with significantly reduced speckle.

    View details for DOI 10.1109/TUFFC.2019.2903795

    View details for PubMedID 30869612

  • Improved Visualization in Difficult-to-Image Stress Echocardiography Patients Using Real-Time Harmonic Spatial Coherence Imaging IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL Hyun, D., Crowley, A. C., LeFevre, M., Cleve, J., Rosenberg, J., Dahl, J. J. 2019; 66 (3): 433–41


    Stress echocardiography is used to detect myocardial ischemia by evaluating cardiovascular function both at rest and at elevated heart rates. Stress echocardiography requires excellent visualization of the left ventricle (LV) throughout the cardiac cycle. However, LV endocardial border visualization is often negatively impacted by high levels of clutter associated with patient obesity, which has risen dramatically worldwide in recent decades. Short-lag spatial coherence (SLSC) imaging has demonstrated reduced clutter in several applications. In this work, a computationally efficient formulation of SLSC was implemented into an object-oriented graphics processing unit-based software beamformer, enabling real-time (>30 frames per second) SLSC echocardiography on a research ultrasound scanner. The system was then used to image 15 difficult-to-image stress echocardiography patients in a comparison study of tissue harmonic imaging (THI) and harmonic spatial coherence imaging (HSCI). Video clips of four standard stress echocardiography views acquired with either THI or HSCI were provided in random shuffled order to three experienced readers. Each reader rated the visibility of 17 LV segments as "invisible," "suboptimally visualized," or "well visualized," with the first two categories indicating a need for contrast agent. In a symmetry test unadjusted for patientwise clustering, HSCI demonstrated a clear superiority over THI ( ). When measured on a per-patient basis, the median total score significantly favored HSCI with . When collapsing the ratings to a two-level scale ("needs contrast" versus "well visualized"), HSCI once again showed an overall superiority over THI, with by McNemar test adjusted for clustering.

    View details for DOI 10.1109/TUFFC.2018.2885777

    View details for Web of Science ID 000461335000003

    View details for PubMedID 30530322

  • Vector Flow Velocity Estimation from Beamsummed Data Using Deep Neural Networks Li, Y., Hyun, D., Dahl, J. J., IEEE IEEE. 2019: 860–63
  • Local speed of sound estimation in tissue using pulse-echo ultrasound: Model-based approach. The Journal of the Acoustical Society of America Jakovljevic, M., Hsieh, S., Ali, R., Chau Loo Kung, G., Hyun, D., Dahl, J. J. 2018; 144 (1): 254


    A model and method to accurately estimate the local speed of sound in tissue from pulse-echo ultrasound data is presented. The model relates the local speeds of sound along a wave propagation path to the average speed of sound over the path, and allows one to avoid bias in the sound-speed estimates that can result from overlying layers of subcutaneous fat and muscle tissue. Herein, the average speed of sound using the approach by Anderson and Trahey is measured, and then the authors solve the proposed model for the local sound-speed via gradient descent. The sound-speed estimator was tested in a series of simulation and ex vivo phantom experiments using two-layer media as a simple model of abdominal tissue. The bias of the local sound-speed estimates from the bottom layers is less than 6.2m/s, while the bias of the matched Anderson's estimates is as high as 66m/s. The local speed-of-sound estimates have higher standard deviation than the Anderson's estimates. When the mean local estimate is computed over a 5-by-5mm region of interest, its standard deviation is reduced to less than 7m/s.

    View details for PubMedID 30075660

  • CLINICAL UTILITY OF FETAL SHORT-LAG SPATIAL COHERENCE IMAGING ULTRASOUND IN MEDICINE AND BIOLOGY Long, W., Hyun, D., Choudhury, K., Bradway, D., McNally, P., Boyd, B., Ellestad, S., Trahey, G. E. 2018; 44 (4): 794–806


    In this study, we evaluate the clinical utility of fetal short-lag spatial coherence (SLSC) imaging. Previous work has documented significant improvements in image quality with fetal SLSC imaging as quantified by measurements of contrast and contrast-to-noise ratio (CNR). The objective of this study was to examine whether this improved technical efficacy is indicative of the clinical utility of SLSC imaging. Eighteen healthy volunteers in their first and second trimesters of pregnancy were scanned using a modified Siemens SC2000 clinical scanner. Raw channel data were acquired for routinely examined fetal organs and used to generate fully matched raw and post-processed harmonic B-mode and SLSC image sequences, which were subsequently optimized for dynamic range and other imaging parameters by a blinded sonographer. Optimized videos were reviewed in matched B-mode and SLSC pairs by three blinded clinicians who scored each video based on overall quality, target conspicuity and border definition. SLSC imaging was highly favored over conventional imaging with SLSC scoring equal to (28.2 ± 10.5%) or higher than (63.9 ± 12.9%) B-mode for video pairs across all examined structures and processing conditions. Multivariate modeling revealed that SLSC imaging is a significant predictor of improved image quality with p ≤ 0.002. Expert-user scores for image quality support the application of SLSC in fetal ultrasound imaging.

    View details for PubMedID 29336851

    View details for PubMedCentralID PMC5827926

  • Improved Sensitivity in Ultrasound Molecular Imaging With Coherence-Based Beamforming. IEEE transactions on medical imaging Hyun, D., Abou-Elkacem, L., Perez, V. A., Chowdhury, S. M., Willmann, J. K., Dahl, J. J. 2018; 37 (1): 241–50


    Ultrasound molecular imaging (USMI) is accomplished by detecting microbubble (MB) contrast agents that have bound to specific biomarkers, and can be used for a variety of imaging applications, such as the early detection of cancer. USMI has been widely utilized in preclinical imaging in mice; however, USMI in humans can be challenging because of the low concentration of bound MBs and the signal degradation caused by the presence of heterogenous soft tissue between the transducer and the lesion. Short-lag spatial coherence (SLSC) beamforming has been proposed as a robust technique that is less affected by poor signal quality than standard delay-and-sum (DAS) beamforming. In this paper, USMI performance was assessed using contrast-enhanced ultrasound imaging combined with DAS (conventional CEUS) and with SLSC (SLSC-CEUS). Each method was characterized by flow channel phantom experiments. In a USMI-mimicking phantom, SLSC-CEUS was found to be more robust to high levels of additive thermal noise than DAS, with a 6dB SNR improvement when the thermal noise level was +6dB or higher. However, SLSC-CEUS was also found to be insensitive to increases in MB concentration, making it a poor choice for perfusion imaging. USMI performance was also measured in vivo using VEGFR2-targeted MBs in mice with subcutaneous human hepatocellular carcinoma tumors, with clinical imaging conditions mimicked using a porcine tissue layer between the tumor and the transducer. SLSC-CEUS improved the SNR in each of ten tumors by an average of 41%, corresponding to 3.0dB SNR. These results indicate that the SLSC beamformer is well-suited for USMI applications because of its high sensitivity and robust properties under challenging imaging conditions.

    View details for DOI 10.1109/TMI.2017.2774814

    View details for PubMedID 29293430

    View details for PubMedCentralID PMC5764183

  • Reverberation Noise Suppression in the Aperture Domain Using 3D Fully Convolutional Neural Networks Brickson, L. L., Hyun, D., Dahl, J. J., IEEE IEEE. 2018
  • High Sensitivity Liver Vasculature Visualization Using a Real-time Coherent Flow Power Doppler (CFPD) Imaging System: A Pilot Clinical Study Li, Y., Hyun, D., Durot, I., Willmann, J. K., Dahl, J. J., IEEE IEEE. 2018
  • Adaptive Grayscale Mapping to Improve Molecular Ultrasound Difference Images Shu, J., Hyun, D., Abou-Elkacem, L., Willmann, J., Dahl, J., IEEE IEEE. 2018
  • Efficient Strategies for Estimating the Spatial Coherence of Backscatter IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL Hyun, D., Crowley, A. L., Dahl, J. J. 2017; 64 (3): 500-513


    The spatial coherence of ultrasound backscatter has been proposed to reduce clutter in medical imaging, to measure the anisotropy of the scattering source, and to improve the detection of blood flow. These techniques rely on correlation estimates that are obtained using computationally expensive strategies. In this paper, we assess the existing spatial coherence estimation methods and propose three computationally efficient modifications: a reduced kernel, a downsampled receive aperture, and the use of an ensemble correlation coefficient. The proposed methods are implemented in simulation and in vivo studies. Reducing the kernel to a single sample improved computational throughput and improved axial resolution. Downsampling the receive aperture was found to have negligible effect on estimator variance, and improved computational throughput by an order of magnitude for a downsample factor of 4. The ensemble correlation estimator demonstrated lower variance than the currently used average correlation. Combining the three methods, the throughput was improved 105-fold in simulation with a downsample factor of 4- and 20-fold in vivo with a downsample factor of 2.

    View details for DOI 10.1109/TUFFC.2016.2634004

    View details for Web of Science ID 000396399400002

    View details for PubMedCentralID PMC5453518

  • Coherence Beamforming and its Applications to the Difficult-to-Image Patient Dahl, J. J., Hyun, D., Li, Y., Jakovljevic, M., Bell, M. L., Long, W. J., Bottenus, N., Kakkad, V., Trahey, G. E., IEEE IEEE. 2017
  • Visualization of Small-Diameter Vessels by Reduction of Incoherent Reverberation With Coherent Flow Power Doppler. IEEE transactions on ultrasonics, ferroelectrics, and frequency control Li, Y. L., Hyun, D., Abou-Elkacem, L., Willmann, J. K., Dahl, J. J. 2016; 63 (11): 1878-1889


    Power Doppler (PD) imaging is a widely used technique for flow detection. Despite the wide use of Doppler ultrasound, limitations exist in the ability of Doppler ultrasound to assess slow flow in the small-diameter vasculature, such as the maternal spiral arteries and fetal villous arteries of the placenta and focal liver lesions. The sensitivity of PD in small vessel detection is limited by the low signal produced by slow flow and the noise associated with small vessels. The noise sources include electronic noise, stationary or slowly moving tissue clutter, reverberation clutter, and off-axis scattering from tissue, among others. In order to provide more sensitive detection of slow flow in small diameter vessels, a coherent flow imaging technique, termed coherent flow PD (CFPD), is characterized and evaluated with simulation, flow phantom experiment studies, and an in vivo animal small vessel detection study. CFPD imaging was introduced as a technique to detect slow blood flow. It has been demonstrated to detect slow flow below the detection threshold of conventional PD imaging using identical pulse sequences and filter parameters. In this paper, we compare CFPD with PD in the detection of blood flow in small-diameter vessels. The results from the study suggest that CFPD is able to provide a 7.5-12.5-dB increase in the signal-to-noise ratio (SNR) over PD images for the same physiological conditions and is less susceptible to reverberation clutter and thermal noise. Due to the increase in SNR, CFPD is able to detect small vessels in high channel noise cases, for which PD was unable to generate enough contrast to observe the vessel.

    View details for PubMedID 27824565

    View details for PubMedCentralID PMC5154731

  • Short-Lag Spatial Coherence Imaging on Matrix Arrays, Part II: Phantom and In Vivo Experiments IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL Jakovljevic, M., Byram, B. C., Hyun, D., Dahl, J. J., Trahey, G. E. 2014; 61 (7): 1113-1122


    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 Imaging on Matrix Arrays, Part I: Beamforming Methods and Simulation Studies IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL Hyun, D., Trahey, G. E., Jakovljevic, M., Dahl, J. J. 2014; 61 (7): 1101-1112


    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

  • A GPU-based real-time spatial coherence imaging system Hyun, D., Trahey, G. E., Dahl, J., Bosch, J. G., Doyley, M. M. SPIE-INT SOC OPTICAL ENGINEERING. 2013

    View details for DOI 10.1117/12.2008686

    View details for Web of Science ID 000325266100041

  • Lesion Detectability in Diagnostic Ultrasound with Short-Lag Spatial Coherence Imaging ULTRASONIC IMAGING Dahl, J. J., Hyun, D., Lediju, M., Trahey, G. E. 2011; 33 (2): 119-133


    We demonstrate a novel imaging technique, named short-lag spatial coherence (SLSC) imaging, which uses short distance (or lag) values of the coherence function of backscattered ultrasound to create images. Simulations using Field II are used to demonstrate the detection of lesions of varying sizes and contrasts with and without acoustical clutter in the backscattered data. B-mode and SLSC imaging are shown to be nearly equivalent in lesion detection, based on the contrast-to-noise ratio (CNR) of the lesion, in noise-free conditions. The CNR of the SLSC image, however, can be adjusted to achieve an optimal value at the expense of image smoothness and resolution. In the presence of acoustic clutter, SLSC imaging yields significantly higher CNR than B-mode imaging and maintains higher image quality than B-mode with increasing noise. Compression of SLSC images is shown to be required under high-noise conditions but is unnecessary under no- and low-noise conditions. SLSC imaging is applied to in vivo imaging of the carotid sheath and demonstrates significant gains in CNR as well as visualization of arterioles in the carotid sheath. SLSC imaging has a potential application to clutter rejection in ultrasonic imaging.

    View details for Web of Science ID 000291961800003

    View details for PubMedID 21710827

  • Development and Evaluation of Pulse Sequences for Freehand ARFI Imaging Doherty, J. R., Dumont, D. M., Hyun, D., Dahl, J. J., Trahey, G. E., IEEE IEEE. 2011: 1281–84

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