Portable Ultrasound Through Compressive Beamforming with Improved Contrast

Mitrovic, Jovan; Pietra, Lynn La; Ignjatović, Željko

doi:10.1109/ultsym.2018.8579978

2018 IEEE International Ultrasonics Symposium (IUS) 2018

DOI: 10.1109/ultsym.2018.8579978

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Portable Ultrasound Through Compressive Beamforming with Improved Contrast

Jovan Mitrovic

Lynn La Pietra

Željko Ignjatović

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2024

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A survey on deep learning in medical ultrasound imaging

Song,

Feng,

Chen

2024

Front. Phys.

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Ultrasound imaging has a history of several decades. With its non-invasive, low-cost advantages, this technology has been widely used in medicine and there have been many significant breakthroughs in ultrasound imaging. Even so, there are still some drawbacks. Therefore, some novel image reconstruction and image analysis algorithms have been proposed to solve these problems. Although these new solutions have some effects, many of them introduce some other side effects, such as high computational complexity in beamforming. At the same time, the usage requirements of medical ultrasound equipment are relatively high, and it is not very user-friendly for inexperienced beginners. As artificial intelligence technology advances, some researchers have initiated efforts to deploy deep learning to address challenges in ultrasound imaging, such as reducing computational complexity in adaptive beamforming and aiding novices in image acquisition. In this survey, we are about to explore the application of deep learning in medical ultrasound imaging, spanning from image reconstruction to clinical diagnosis.

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A survey on deep learning in medical ultrasound imaging

Song,

Feng,

Chen

2024

Front. Phys.

View full text Add to dashboard Cite

show abstract

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Portable Ultrasound Through Compressive Beamforming with Improved Contrast

Cited by 1 publication

References 10 publications

A survey on deep learning in medical ultrasound imaging

A survey on deep learning in medical ultrasound imaging

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