Hoda Hashemi

All Publications

• Real-Time Reverberation Suppression in Ultrasound Channel Signals Using a Permuted 2D Convolutional Neural Network. Ultrasonic imaging Brickson, L. L., Hyun, D., Hashemi, H. S., Simson, W. A., Antil, N., Pinton, G., Dahl, J. J. 2026: 1617346261467350

  Abstract

  Diffuse reverberation noise in ultrasound imaging arises from multiple reflections or secondary scattering of an echo, such as when a strong echo reflects multiple times between a fascial layer and the transducer. Unlike coherent reverberation artifacts, such as multiple reflections within an arterial wall that produce obvious ringdown in the image, these multiple reflections produce speckle-like artifacts that overlay and obscure anatomical targets and are difficult to distinguish from tissue speckle. This noise also degrades image reconstruction and interferes with imaging techniques that rely on displacement or time shifts in the ultrasonic echoes. This work introduces a permuted 2D convolutional neural network (2DCNN) for real-time reverberation suppression in ultrasound channel signals. This technique can be used to improve B-mode image quality or can be used as a pre-processing filter for techniques that require channel or beamsummed signals. The proposed architecture offers significant computational advantages over the previously implementations using 3D convolutional networks, enabling real-time implementation on existing hardware at 15 fps. The 2DCNN was trained on an enhanced dataset that combines Field II and Fullwave simulations, incorporating a broad range of acoustic affects, including reverberation noise, aberration, and attenuation. Validation on liver and kidney scans from 15 volunteers demonstrated improvements in image quality metrics related to the removal of diffuse reverberation noise, including increasing contrast, generalized contrast-to-noise ratio (GCNR), and lag-one coherence (LOC).

  View details for DOI 10.1177/01617346261467350

  View details for PubMedID 42473910

• Enhancing Ultrasound Molecular Imaging: Toward Real-Time RPCA-Based Filtering to Differentiate Bound and Free Microbubbles IEEE TRANSACTIONS ON ULTRASONICS Hashemi, H. S., Hyun, D., Nguyen, N., Baek, J., Natarajan, A., Tabesh, F., Andrzejek, A., Paulmurugan, R., Dahl, J. J. 2026; 73 (2): 183-193

  Abstract

  Ultrasound molecular imaging (UMI) is an advanced imaging modality that shows promise in detecting cancer at early stages. It uses microbubbles as contrast agents, which are functionalized to bind to cancer biomarkers overexpressed on endothelial cells. A major challenge in UMI is isolating bound microbubble signal, which represents the molecular imaging signal, from that of free-floating microbubbles, which is considered background noise. In this work, we propose a fast GPU-based method using robust principal component analysis (RPCA) to distinguish bound microbubbles from free-floating ones. We explore the method using simulations and measure the accuracy using the Dice coefficient and RMS error as functions of the number of frames used in RPCA reconstruction. Experiments using stationary and flowing microbubbles in tissue-mimicking phantoms were used to validate the method. Additionally, the method was applied to data from ten transgenic mouse models of breast cancer development, injected with B7-H3 targeted microbubbles, and two mice injected with non-targeted microbubbles. The results showed that RPCA using 20 frames achieved a Dice score of 0.95 and a computation time of 0.2 seconds, indicating that 20 frames is potentially suitable for real-time implementation. On in vivo data, RPCA using 20 frames achieved a Dice score of 0.82 with DTE, indicating good agreement between the two, given the limitations of each method.

  View details for DOI 10.1109/TUSON.2025.3647590

  View details for Web of Science ID 001815829500011

  View details for PubMedID 42078652

  View details for PubMedCentralID PMC13132560

• Real-Time Convolutional Neural Network for Nondestructive Detection of Targeted Microbubbles in Ultrasound Molecular Imaging Hashemi, H. S., Nguyen, N., Baek, J., Abdullah, R., Natarajan, A., Tabesh, F., Hyun, D., Paulmurugan, R., Dahl, J. J. edited by Boehm, C., Mehrmohammadi, M., Xiang, S. L. SPIE-INT SOC OPTICAL ENGINEERING. 2026

  View details for DOI 10.1117/12.3086168

  View details for Web of Science ID 001767133000033

• Enhancing Ultrasound Molecular Imaging: Toward Real-Time RPCA-Based Filtering to Differentiate Bound and Free Microbubbles. IEEE transactions on ultrasonics Hashemi, H. S., Hyun, D., Nguyen, N., Baek, J., Natarajan, A., Tabesh, F., Andrzejek, A., Paulmurugan, R., Dahl, J. J. 2025

  Abstract

  Ultrasound molecular imaging (UMI) is an advanced imaging modality that shows promise in detecting cancer at early stages. It uses microbubbles as contrast agents, which are functionalized to bind to cancer biomarkers overexpressed on endothelial cells. A major challenge in UMI is isolating bound microbubble signal, which represents the molecular imaging signal, from that of free-floating microbubbles, which is considered background noise. In this work, we propose a fast GPU-based method using robust principal component analysis (RPCA) to distinguish bound microbubbles from free-floating ones. We explore the method using simulations and measure the accuracy using the Dice coefficient and RMS error as functions of the number of frames used in RPCA reconstruction. Experiments using stationary and flowing microbubbles in tissue-mimicking phantoms were used to validate the method. Additionally, the method was applied to data from ten transgenic mouse models of breast cancer development, injected with B7-H3 targeted microbubbles, and two mice injected with non-targeted microbubbles. The results showed that RPCA using 20 frames achieved a Dice score of 0.95 and a computation time of 0.2 seconds, indicating that 20 frames is potentially suitable for real-time implementation. On in vivo data, RPCA using 20 frames achieved a Dice score of 0.82 with DTE, indicating good agreement between the two, given the limitations of each method.

  View details for DOI 10.1109/tuson.2025.3647590

  View details for PubMedID 42078652

  View details for PubMedCentralID PMC13132560

• UltraFlex: Iterative Model-Based Ultrasonic Flexible-Array Shape Calibration IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL Frey, B. N., Hyun, D., Simson, W., Zhuang, L., Hashemi, H. S., Schneider, M., Dahl, J. J. 2025; 72 (11): 1462-1475

  Abstract

  UltraFlex is an iterative model-based ultrasonic flexible-array shape calibration framework that uses automatic differentiation. This work evaluates array shape calibration model performance while examining multiple image quality metrics: speckle brightness, envelope entropy, coherence factor, lag-one coherence, common-midpoint correlation coefficient (CMCC), and common-midpoint phase error (CMPE). The accuracy of these image quality metrics was evaluated on simulated phantoms using a variety of array shapes. Experimental phantom and in vivo liver datasets were also investigated using transducers with known geometries. While speckle brightness, envelope entropy, and coherence factor enable model convergence under many conditions, lag-one coherence, CMCC, and CMPE enable more accurate element position estimations and improved visual ultrasound image focusing quality. Furthermore, the models based on the CMCC and phase-error quality metrics are the most robust against additive white noise while achieving median mean Euclidean errors (MEEs) of 3.7 μm for simulation, 29.7 μm for phantom, and 69.0 μm for in vivo liver data. These array shape calibration results show promise for future development of experimental flexible- and wearableultrasonic arrays.

  View details for DOI 10.1109/TUFFC.2025.3627525

  View details for Web of Science ID 001629793500002

  View details for PubMedID 41171672

• MBFormer: A Transformer model for 3D Time-Series Data Processing to Improve Bound Bubble Detection in Nondestructive Ultrasound Molecular Imaging Baek, J., Lee, J., Hashemi, H. S., Natarajan, A., Tabesh, F., Paulmurugan, R., Dahl, J. J., IEEE IEEE. 2025

  View details for DOI 10.1109/IUS62464.2025.11201536

  View details for Web of Science ID 001719884800271

• Ultrasound Molecular Imaging: A Quantitative Metric for Vascular-Independent Targeted Microbubble Binding Hashemi, H. S., Baek, J., Nguyen, N., Natarajan, A., Tabesh, F., Paulmurugan, R., Dahl, J. J., IEEE IEEE. 2025

  View details for DOI 10.1109/IUS62464.2025.11201656

  View details for Web of Science ID 001719884800388

• Enhancing Ultrasound Molecular Imaging: RPCA-Based Filtering to Differentiate Tumor-Bound and Free Microbubbles Hashemi, H. S., Hyun, D., Baek, J., Natarajan, A., Tabesh, F., Paulmurugan, R., Dahl, J. J., IEEE IEEE. 2024

  View details for DOI 10.1109/UFFC-JS60046.2024.10793633

  View details for Web of Science ID 001428150100142

• Ultrafast 3-D Photoacoustic System Development using a Matrix Array Transducer Moradi, H., Hashemi, H., Vousten, V., Rohling, R., Salcudean, S. edited by Oraevsky, A. A., Wang, L. V. SPIE-INT SOC OPTICAL ENGINEERING. 2024

  View details for DOI 10.1117/12.3003328

  View details for Web of Science ID 001234513800020

• 3-D Ultrafast Shear Wave Absolute Vibro-Elastography Using a Matrix Array Transducer IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL Hashemi, H. S., Mohammed, S. K., Zeng, Q., Azar, R., Rohling, R. N., Salcudean, S. E. 2023; 70 (9): 1039-1053

  Abstract

  Real-time ultrasound imaging plays an important role in ultrasound-guided interventions. The 3-D imaging provides more spatial information compared to conventional 2-D frames by considering the volumes of data. One of the main bottlenecks of 3-D imaging is the long data acquisition time, which reduces practicality and can introduce artifacts from unwanted patient or sonographer motion. This article introduces the first shear wave absolute vibro-elastography (S-WAVE) method with real-time volumetric acquisition using a matrix array transducer. In S-WAVE, an external vibration source generates mechanical vibrations inside the tissue. The tissue motion is then estimated and used in solving a wave equation inverse problem to provide the tissue elasticity. A matrix array transducer is used with a Verasonics ultrasound machine and a frame rate of 2000 volumes/s to acquire 100 radio frequency (RF) volumes in 0.05 s. Using plane wave (PW) and compounded diverging wave (CDW) imaging methods, we estimate axial, lateral, and elevational displacements over 3-D volumes. The curl of the displacements is used with local frequency estimation to estimate elasticity in the acquired volumes. Ultrafast acquisition extends substantially the possible S-WAVE excitation frequency range, now up to 800 Hz, enabling new tissue modeling and characterization. The method was validated on three homogeneous liver fibrosis phantoms and on four different inclusions within a heterogeneous phantom. The homogeneous phantom results show less than 8% (PW) and 5% (CDW) difference between the manufacturer values and the corresponding estimated values over a frequency range of 80-800 Hz. The estimated elasticity values for the heterogeneous phantom at 400-Hz excitation frequency show the average errors of 9% (PW) and 6% (CDW) compared to the provided average values by magnetic resonance elastography (MRE). Furthermore, both imaging methods were able to detect the inclusions within the elasticity volumes. An ex vivo study on a bovine liver sample shows less than 11% (PW) and 9% (CDW) difference between the estimated elasticity ranges by the proposed method and the elasticity ranges provided by MRE and acoustic radiation force impulse (ARFI).

  View details for DOI 10.1109/TUFFC.2023.3280450

  View details for Web of Science ID 001059175300012

  View details for PubMedID 37235463

• Real-Time 3D Ultrafast Shear Wave Absolute Vibro-Elastography Hashemi, H. S., Mohammed, S. K., Azar, R., Rohling, R. N., Salcudean, S. E. edited by Boehm, C., Bottenus, N. SPIE-INT SOC OPTICAL ENGINEERING. 2023

  View details for DOI 10.1117/12.2654011

  View details for Web of Science ID 001011440800006

• Model-Based Quantitative Elasticity Reconstruction Using ADMM IEEE TRANSACTIONS ON MEDICAL IMAGING Mohammed, S., Honarvar, M., Zeng, Q., Hashemi, H., Rohling, R., Kozlowski, P., Salcudean, S. 2022; 41 (11): 3039-3052

  Abstract

  We introduce two model-based iterative methods to obtain shear modulus images of tissue using magnetic resonance elastography. The first method jointly finds the displacement field that best fits tissue displacement data and the corresponding shear modulus. The displacement satisfies a viscoelastic wave equation constraint, discretized using the finite element method. Sparsifying regularization terms in both shear modulus and displacement are used in the cost function minimized for the best fit. The second method extends the first method for multifrequency tissue displacement data. The formulated problems are bi-convex. Their solution can be obtained iteratively by using the alternating direction method of multipliers. Sparsifying regularizations and the wave equation constraint filter out sensor noise and compressional waves. Our methods do not require bandpass filtering as a preprocessing step and converge fast irrespective of the initialization. We evaluate our new methods in multiple in silico and phantom experiments, with comparisons with existing methods, and we show improvements in contrast to noise and signal-to-noise ratios. Results from an in vivo liver imaging study show elastograms with mean elasticity comparable to other values reported in the literature.

  View details for DOI 10.1109/TMI.2022.3178072

  View details for Web of Science ID 000876061700006

  View details for PubMedID 35617177

• Breast Cancer Detection Using Multimodal Time Series Features From Ultrasound Shear Wave Absolute Vibro-Elastography IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS Shao, Y., Hashemi, H. S., Gordon, P., Warren, L., Wang, J., Rohling, R., Salcudean, S. 2022; 26 (2): 704-714

  Abstract

  In shear wave absolute vibro-elastography (S-WAVE), a steady-state multi-frequency external mechanical excitation is applied to tissue, while a time-series of ultrasound radio-frequency (RF) data are acquired. Our objective is to determine the potential of S-WAVE to classify breast tissue lesions as malignant or benign. We present a new processing pipeline for feature-based classification of breast cancer using S-WAVE data, and we evaluate it on a new data set collected from 40 patients. Novel bi-spectral and Wigner spectrum features are computed directly from the RF time series and are combined with textural and spectral features from B-mode and elasticity images. The Random Forest permutation importance ranking and the Quadratic Mutual Information methods are used to reduce the number of features from 377 to 20. Support Vector Machines and Random Forest classifiers are used with leave-one-patient-out and Monte Carlo cross-validations. Classification results obtained for different feature sets are presented. Our best results (95% confidence interval, Area Under Curve = 95%±1.45%, sensitivity = 95%, and specificity = 93%) outperform the state-of-the-art reported S-WAVE breast cancer classification performance. The effect of feature selection and the sensitivity of the above classification results to changes in breast lesion contours is also studied. We demonstrate that time-series analysis of externally vibrated tissue as an elastography technique, even if the elasticity is not explicitly computed, has promise and should be pursued with larger patient datasets. Our study proposes novel directions in the field of elasticity imaging for tissue classification.

  View details for DOI 10.1109/JBHI.2021.3103676

  View details for Web of Science ID 000772331200021

  View details for PubMedID 34375294

• 3D Global Time-Delay Estimation for Shear-Wave Absolute Vibro-Elastography of the Placenta Hashemi, H. S., Honarvar, M., Salcudean, T., Rohling, R., IEEE IEEE. 2020: 2079-2083

  Abstract

  The placenta is a vital organ for growth and development of the fetus. Shear Wave Absolute Vibro-Elastography (SWAVE) is a new elastography technique proposed to detect placenta disorders. Elastography involves applying a force on the tissue and measuring the resulting tissue deformation. All types of compression cause the tissue to expand in three directions given the biological tissues are nearly incompressible. Hence, 3D displacement estimation should lead to the most accurate elasticity reconstruction compared to the traditional 1D methods. Previous studies estimated 3D displacements over ultrasound volumes mostly for quasi-static compression to generate strain images. However, accurate displacement tracking of dynamic motion continues to be a challenge. In this work, a novel volumetric regularized algorithm, 3D GLobal Ultrasound Elastography (GLUE3D), is presented to estimate the 3D displacement over a volume of ultrasound data, following by a 3D Young's modulus reconstruction. The proposed method outperforms the previous 2D method over a volume and is compared with a 3D technique using phantom data for which the elasticity are provided by the values from magnetic resonance elastography on the same phantom and also the manufacturer reference numbers. We then present Young's modulus reconstruction results obtained from clinical data of placenta which shows more uniform elasticity maps compared to the traditional 1D displacement measurements over a volume of ultrasound data. Furthermore, the dependency of the elasticity values to the frequency is investigated in this study.

  View details for Web of Science ID 000621592202102

  View details for PubMedID 33018415

• Assessment of Mechanical Properties of Tissue in Breast Cancer-Related Lymphedema Using Ultrasound Elastography IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL Hashemi, H. S., Fallone, S., Boily, M., Towers, A., Kilgour, R. D., Rivaz, H. 2019; 66 (3): 541-550

  Abstract

  Breast cancer-related lymphedema is a consequence of a malfunctioning lymphatic drainage system resulting from surgery or some other form of treatment. In the initial stages, minor and reversible increases in the fluid volume of the arm are evident. As the stages progress over time, the underlying pathophysiology dramatically changes with an irreversible increase in arm volume most likely due to a chronic local inflammation leading to adipose tissue hypertrophy and fibrosis. Clinicians have subjective ways to stage the degree and severity such as the pitting test which entails manually comparing the elasticity of the affected and unaffected arms. Several imaging modalities can be used but ultrasound appears to be the most preferred because it is affordable, safe, and portable. Unfortunately, ultrasonography is not typically used for staging lymphedema, because the appearance of the affected and unaffected arms is similar in B-mode ultrasound images. However, novel ultrasound techniques have emerged, such as elastography, which may be able to identify changes in mechanical properties of the tissue related to detection and staging of lymphedema. This paper presents a novel technique to compare the mechanical properties of the affected and unaffected arms using quasi-static ultrasound elastography to provide an objective alternative to the current subjective assessment. Elastography is based on time delay estimation (TDE) from ultrasound images to infer displacement and mechanical properties of the tissue. We further introduce a novel method for TDE by incorporating higher order derivatives of the ultrasound data into a cost function and propose a novel optimization approach to efficiently minimize the cost function. This method works reliably with our challenging patient data. We collected radio frequency ultrasound data from both arms of seven patients with stage 2 lymphedema, at six different locations in each arm. The ratio of strain in skin, subcutaneous fat, and skeletal muscle divided by strain in the standoff gel pad was calculated in the unaffected and affected arms. The p -values using a Wilcoxon sign-rank test for the skin, subcutaneous fat, and skeletal muscle were 1.24×10-5 , 1.77×10-8 , and 8.11×10-7 respectively, showing differences between the unaffected and affected arms with a very high level of significance.

  View details for DOI 10.1109/TUFFC.2018.2876056

  View details for Web of Science ID 000461335000013

  View details for PubMedID 30334756

• HIGH-DYNAMIC-RANGE ULTRASOUND: APPLICATION FOR IMAGING TENDON PATHOLOGY ULTRASOUND IN MEDICINE AND BIOLOGY Xiao, Y., Boily, M., Hashemi, H., Rivaz, H. 2018; 44 (7): 1525-1532

  Abstract

  Raw ultrasound (US) signal has a very high dynamic range (HDR) and, as such, is compressed in B-mode US using a logarithmic function to fit within the dynamic range of digital displays. However, in some cases, hyper-echogenic tissue can be overexposed at high gain levels with the loss of hypo-echogenic detail at low gain levels. This can cause the loss of anatomic detail and tissue texture and frequent and inconvenient gain adjustments, potentially affecting the diagnosis. To mitigate these drawbacks, we employed tone mapping operators (TMOs) in HDR photography to create HDR US. We compared HDR US produced from three different popular TMOs (Reinhard, Drago and Durand) against conventional US using a simulated US phantom and in vivo images of patellar tendon pathologies. Based on visual inspection and assessments of structural fidelity, image entropy and contrast-to-noise ratio metrics, Reinhard and Drago TMOs substantially improved image detail and texture.

  View details for DOI 10.1016/j.ultrasmedbio.2018.03.004

  View details for Web of Science ID 000432372600022

  View details for PubMedID 29628224

• ULTRASOUND ELASTOGRAPHY OF BREAST CANCER-RELATED LYMPHEDEMA Hashemi, H. S., Fallone, S., Boily, M., Towers, A., Kilgour, R. D., Rivaz, H., IEEE IEEE. 2018: 1491-1495

  View details for Web of Science ID 000455045600343

• Global Time-Delay Estimation in Ultrasound Elastography IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL Hashemi, H., Rivaz, H. 2017; 64 (10): 1625-1636

  Abstract

  A critical step in quasi-static ultrasound elastography is the estimation of time delay between two frames of radio-frequency (RF) data that are obtained while the tissue is undergoing deformation. This paper presents a novel technique for time-delay estimation (TDE) of all samples of RF data simultaneously, thereby exploiting all the information in RF data for TDE. A nonlinear cost function that incorporates similarity of RF data intensity and prior information of displacement continuity is formulated. Optimization of this function involves searching for TDE of all samples of the RF data, rendering the optimization intractable with conventional techniques given that the number of variables can be approximately one million. Therefore, the optimization problem is converted to a sparse linear system of equations, and is solved in real time using a computationally efficient optimization technique. We call our method GLobal Ultrasound Elastography (GLUE), and compare it to dynamic programming analytic minimization (DPAM) and normalized cross correlation (NCC) techniques. Our simulation results show that the contrast-to-noise ratio (CNR) values of the axial strain maps are 4.94 for NCC, 14.62 for DPAM, and 26.31 for GLUE. Our results on experimental data from tissue mimicking phantoms show that the CNR values of the axial strain maps are 1.07 for NCC, 16.01 for DPAM, and 18.21 for GLUE. Finally, our results on in vivo data show that the CNR values of the axial strain maps are 3.56 for DPAM and 13.20 for GLUE.

  View details for DOI 10.1109/TUFFC.2017.2717933

  View details for Web of Science ID 000412634700019

  View details for PubMedID 28644804

• Ultrasound Elastography: Efficient Estimation of Tissue Displacement Using an Affine Transformation Model Hashemi, H., Boily, M., Martineau, P. A., Rivaz, H. edited by Duric, N., Heyde, B. SPIE-INT SOC OPTICAL ENGINEERING. 2017

  View details for DOI 10.1117/12.2254297

  View details for Web of Science ID 000404887800002