Deep Learning in Ultrasound Imaging

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Adaptive Ultrasound Beamforming Using Deep Learning

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Transfer Learning in Breast Cancer Diagnoses via Ultrasound Imaging

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Measuring Image Resolution in Ultrasound Localization Microscopy

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Local interpretable model-agnostic explanation approach for medical imaging analysis: A systematic literature review

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Deep Learning for Ultrasound Image Formation: CUBDL Evaluation Framework and Open Datasets

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Ultrasound image reconstruction from plane wave radio-frequency data by self-supervised deep neural network

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COVID-19 classification of X-ray images using deep neural networks

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CNN-Based Image Reconstruction Method for Ultrafast Ultrasound Imaging

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Machine learning methods for histopathological image analysis: updates in 2024

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Solving inverse-PDE problems with physics-aware neural networks

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High resolution 3D ultrasonic breast imaging by time-domain full waveform inversion

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Integrating Domain Knowledge Into Deep Networks for Lung Ultrasound With Applications to COVID-19

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Breast Cancer Prediction Empowered with Fine-Tuning

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Deep Learning of Spatiotemporal Filtering for Fast Super-Resolution Ultrasound Imaging

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Real-time denoising of ultrasound images based on deep learning

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Learning Sub-Sampling and Signal Recovery With Applications in Ultrasound Imaging

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A survey on deep learning in medical ultrasound imaging

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Grad-CAM (Gradient-weighted Class Activation Mapping): A systematic literature review

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Image Quality Enhancement Using a Deep Neural Network for Plane Wave Medical Ultrasound Imaging

Qi, Y., Guo, Y., & Wang, Y. (2020) · IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control · doi:10.1109/tuffc.2020.3023154 · Cited by 55

CohereNet: A Deep Learning Architecture for Ultrasound Spatial Correlation Estimation and Coherence-Based Beamforming

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Landmark tracking in liver US images using cascade convolutional neural networks with long short-term memory

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Speckle noise reduction for medical ultrasound images based on cycle-consistent generative adversarial network

Liu, J., Li, C., Liu, L., Chen, H., Han, H., Zhang, B., & Zhang, Q. (2023) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2023.105150 · Cited by 51

Learning sub-sampling and signal recovery with applications in ultrasound imaging

Huijben, I. A. M., Veeling, B. S., Janse, C. K., Mischi, M. M., & Sloun, R. R. V. (2019) · TU/e Research Portal · Cited by 51

Model-based reinforcement learning for ultrasound-driven autonomous microrobots

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Ultrasound Signal Processing: From Models to Deep Learning

Luijten, B., Chennakeshava, N., Eldar, Y. C., Mischi, M., & van Sloun, R. J. G. (2023) · Ultrasound in Medicine & Biology · doi:10.1016/j.ultrasmedbio.2022.11.003 · Cited by 52

Learned SPARCOM: unfolded deep super-resolution microscopy

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Deep learning in ultrasound elastography imaging: A review

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Dehazing Ultrasound Using Diffusion Models

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Technology trends and applications of deep learning in ultrasonography: image quality enhancement, diagnostic support, and improving workflow efficiency

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Plane-Wave Image Reconstruction via Generative Adversarial Network and Attention Mechanism

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Challenge on Ultrasound Beamforming with Deep Learning (CUBDL)

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Literature analysis of artificial intelligence in biomedicine

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Efficient design method for terahertz broadband metasurface patterns via deep learning

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Detection of Gallbladder Disease Types Using Deep Learning: An Informative Medical Method

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Phase Asymmetry Ultrasound Despeckling With Fractional Anisotropic Diffusion and Total Variation

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A Comprehensive Survey of Machine Learning Applied to Radar Signal ProcessingPreprint

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An Upgraded Siamese Neural Network for Motion Tracking in Ultrasound Image Sequences

Bharadwaj, S., Prasad, S., & Almekkawy, M. K. (2021) · IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control · doi:10.1109/tuffc.2021.3095299 · Cited by 42

Model-Based Deep Learning: Key Approaches and Design Guidelines

Shlezinger, N., Whang, J., Eldar, Y. C., & Dimakis, A. G. (2021) · IEEE Data Science Workshop (DSW) · doi:10.1109/dslw51110.2021.9523403 · Cited by 42

Comparing deep learning-based automatic segmentation of breast masses to expert interobserver variability in ultrasound imaging

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The role of artificial intelligence in electrodiagnostic and neuromuscular medicine: Current state and future directions

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Knowledge distillation and teacher–student learning in medical imaging: Comprehensive overview, pivotal role, and future directions

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Artificial intelligence-assisted ultrasound image analysis to discriminate early breast cancer in Chinese population: a retrospective, multicentre, cohort study

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Deep reconstruction of high-quality ultrasound images from raw plane-wave data: A simulation and in vivo study

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An adaptive watershed segmentation based medical image denoising using deep convolutional neural networks

Annavarapu, A., & Borra, S. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.106119 · Cited by 42

A deep-learning framework for metacarpal-head cartilage-thickness estimation in ultrasound rheumatological images

Fiorentino, M. C., Cipolletta, E., Filippucci, E., Grassi, W., Frontoni, E., & Moccia, S. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.105117 · Cited by 35

Using Deep Learning to Detect the Presence and Location of Hemoperitoneum on the Focused Assessment with Sonography in Trauma (FAST) Examination in Adults

Leo, M. M., Potter, İ. Y., Zahiri, M., Vaziri, A., Jung, C. F., & Feldman, J. A. (2023) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-023-00845-6 · Cited by 35

A dual-branch and dual attention transformer and CNN hybrid network for ultrasound image segmentation

Zhang, C., Wang, L., Wei, G., Kong, Z., & Qiu, M. (2024) · Frontiers in Physiology · doi:10.3389/fphys.2024.1432987 · Cited by 35

ApodNet: Learning for High Frame Rate Synthetic Transmit Aperture Ultrasound Imaging

Chen, Y., Liu, J., Luó, X., & Luo, J. (2021) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2021.3084821 · Cited by 33

CapsCovNet: A Modified Capsule Network to Diagnose COVID-19 From Multimodal Medical Imaging

Saif, A. F. M., Imtiaz, T., Rifat, S., Shahnaz, C., Zhu, W., & Ahmad, M. O. (2021) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2021.3104791 · Cited by 32

Revolutionizing Medical Practice: The Impact of Artificial Intelligence (AI) on Healthcare

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Deep Tomographic Image Reconstruction: Yesterday, Today, and Tomorrow—Editorial for the 2nd Special Issue “Machine Learning for Image Reconstruction”

Wang, G., Jacob, M., Mou, X., Shi, Y., & Eldar, Y. C. (2021) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2021.3115547 · Cited by 28

Comparison of Intraoperative Ultrasound B-Mode and Strain Elastography for the Differentiation of Glioblastomas From Solitary Brain Metastases. An Automated Deep Learning Approach for Image Analysis

Cepeda, S., García-García, S., Arrese, I., Fernández-Pérez, G. C., Velasco-Casares, M., Fajardo-Puentes, M., Zamora, T., & Sarabia, R. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2020.590756 · Cited by 27

Designing Interpretable Recurrent Neural Networks for Video Reconstruction via Deep Unfolding

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Rethinking Ultrasound Augmentation: A Physics-Inspired Approach

Tirindelli, M., Eilers, C., Simson, W. A., Paschali, M., Azampour, M. F., & Navab, N. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-87237-3_66 · Cited by 27

Deep Learning for COVID-19 Diagnosis from CT Images

Loddo, A., Pili, F., & Ruberto, C. D. (2021) · Applied Sciences · doi:10.3390/app11178227 · Cited by 27

Ultrasound image super-resolution reconstruction based on semi-supervised CycleGAN

Gao, F., Li, B., Chen, L., Wei, X., Shang, Z., & Liu, C. (2023) · Ultrasonics · doi:10.1016/j.ultras.2023.107177 · Cited by 26

Malignant thoracic lymph node classification with deep convolutional neural networks on real-time endobronchial ultrasound (EBUS) images

Yong, S. H., Lee, S. H., Oh, S.-I., Keum, J.-S., Kim, K. N., Park, M. S., Chang, Y. S., & Kim, E. Y. (2022) · Translational Lung Cancer Research · doi:10.21037/tlcr-21-870 · Cited by 25

Structured LISTA for Multidimensional Harmonic Retrieval

Fu, R., Liu, Y., Huang, T., & Eldar, Y. C. (2021) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2021.3086593 · Cited by 24

Image Classification-Based Defect Detection of Railway Tracks Using Fiber Bragg Grating Ultrasonic Sensors

Dang, D.-Z., Lai, C.-C., Ni, Y., Zhao, Q. L., Su, B., & Zhou, Q. (2022) · Applied Sciences · doi:10.3390/app13010384 · Cited by 26

A Learning-Based Microultrasound System for the Detection of Inflammation of the Gastrointestinal Tract

Yang, S., Lemke, C., Cox, B. F., Newton, I. P., Näthke, I. S., & Cochran, S. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2020.3021560 · Cited by 24

Domain Adaptation in Intelligent Ultrasonic Logging Tool: From Microseismic to Pulse-Echo

Gao, X., Shi, Y., Zhu, Q., Ли, Ж., Sun, H., Yao, Z., & Zhang, W. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3050154 · Cited by 22

DNN-based Speed-of-Sound Reconstruction for Automated Breast Ultrasound

Jush, F. K., Biele, M., Dueppenbecker, P. M., Schmidt, O., & Maier, A. (2020) · IEEE International Ultrasonics Symposium · doi:10.1109/ius46767.2020.9251579 · Cited by 22

Deep Unrolled Recovery in Sparse Biological Imaging: Achieving fast, accurate results

Sahel, Y. B., Bryan, J. P., Cleary, B., Farhi, S. L., & Eldar, Y. C. (2022) · IEEE Signal Processing Magazine · doi:10.1109/msp.2021.3129995 · Cited by 22

Adaptive beamforming based on minimum variance (ABF-MV) using deep neural network for ultrafast ultrasound imaging

Wang, W., He, Q., Zhang, Z., & Feng, Z. (2022) · Ultrasonics · doi:10.1016/j.ultras.2022.106823 · Cited by 22

A robust cascaded deep neural network for image reconstruction of single plane wave ultrasound RF data

Wasih, M., Ahmad, S., & Almekkawy, M. K. (2023) · Ultrasonics · doi:10.1016/j.ultras.2023.106981 · Cited by 22

WSRGAN: A wavelet-based GAN for super-resolution of plane-wave ultrasound images without sampling loss

Lyu, Y., Xu, Y., Yang, C., Jiang, X., Zhao, X., & Zhu, X. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.107384 · Cited by 22

Denoising Plane Wave Ultrasound Images Using Diffusion Probabilistic Models

Asgariandehkordi, H., Goudarzi, S., Sharifzadeh, M., Basarab, A., & Rivaz, H. J. (2024) · IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control · doi:10.1109/tuffc.2024.3448209 · Cited by 28

Functional ultrasound imaging: A useful tool for functional connectomics?

de Paz, J. M. M., & Macé, É. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118722 · Cited by 19

B-Line Detection and Localization in Lung Ultrasound Videos Using Spatiotemporal Attention

Kerdegari, H., Nhat, P. T. H., McBride, A., Pisani, L., Nguyen, H. V., Thuy, D. B., Razavi, R., Thwaites, L., Yacoub, S., & Gómez, A. (2021) · Applied Sciences · doi:10.3390/app112411697 · Cited by 21

A review on the current progress of layered double hydroxide application in biomedical sectors

Karmakar, A. K., Hasan, M. S., Sreemani, A., Jayanta, A. D., Hasan, M. M., Tithe, N. A., & Biswas, P. (2022) · The European Physical Journal Plus · doi:10.1140/epjp/s13360-022-02993-0 · Cited by 22

Current Advances in Computational Lung Ultrasound Imaging: A Review

Yang, T., Karakuş, O., Anantrasirichai, N., & Achim, A. (2022) · IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control · doi:10.1109/tuffc.2022.3221682 · Cited by 22

Ultrasound Image Reconstruction with Denoising Diffusion Restoration Models

Zhang, Y., Huneau, C., Idier, J., & Mateus, D. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-53767-7_19 · Cited by 26

Automated detection and localization of pericardial effusion from point-of-care cardiac ultrasound examination

Potter, İ. Y., Leo, M. M., Vaziri, A., & Feldman, J. A. (2023) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-023-02855-6 · Cited by 22

Electromechanical Wave Imaging With Machine Learning for Automated Isochrone Generation

Melki, L., Tourni, M., & Konofagou, E. E. (2021) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2021.3074808 · Cited by 20

Unsupervised ResNet-Inspired Beamforming Design Using Deep Unfolding Technique

Lin, C.-H., Lee, Y.-T., Chung, W., Lin, S., & Lee, T.-S. (2020) · Globecom · doi:10.1109/globecom42002.2020.9322638 · Cited by 18

Learned Super Resolution Ultrasound for Improved Breast Lesion Characterization

Bar-Shira, O., Grubstein, A., Rapson, Y., Suhami, D., Atar, E., Peri-Hanania, K., Rosen, R., & Eldar, Y. C. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-87234-2_11 · Cited by 18

Advanced Carriers for Precise Delivery and Therapeutic Mechanisms of Traditional Chinese Medicines: Integrating Spatial Multi‐Omics and Delivery Visualization

Zhang, Y., Lü, Z., Guo, J., Wáng, Q., Zhang, X., Yang, H., & Li, X. (2025) · Advanced Healthcare Materials · doi:10.1002/adhm.202403698 · Cited by 19

Enhancing fetal ultrasound image quality and anatomical plane recognition in low-resource settings using super-resolution models

Boumeridja, H., Ammar, M., Alzubaidi, M. S., Mahmoudi, S., Benamer, L. N., Agus, M., Househ, M. S., Lekadir, K., & Daho, M. E. H. (2025) · Scientific Reports · doi:10.1038/s41598-025-91808-0 · Cited by 18

Deep Unfolding of Image Denoising by Quantum Interactive Patches

Dutta, S., Basarab, A., Georgeot, B., & Kouamé, D. (2022) · Proceedings - International Conference on Image Processing · doi:10.1109/icip46576.2022.9897959 · Cited by 16

On a Deep Learning Method of Estimating Reservoir Porosity

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A Deep-Unfolded Reference-Based RPCA Network For Video Foreground-Background Separation

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