AIMC Topic: Ultrasonography

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Prospective Real-Time Validation of a Lung Ultrasound Deep Learning Model in the ICU.

Critical care medicine
OBJECTIVES: To evaluate the accuracy of a bedside, real-time deployment of a deep learning (DL) model capable of distinguishing between normal (A line pattern) and abnormal (B line pattern) lung parenchyma on lung ultrasound (LUS) in critically ill p...

Image Noise Removal in Ultrasound Breast Images Based on Hybrid Deep Learning Technique.

Sensors (Basel, Switzerland)
Rapid improvements in ultrasound imaging technology have made it much more useful for screening and diagnosing breast problems. Local-speckle-noise destruction in ultrasound breast images may impair image quality and impact observation and diagnosis....

Application of Deep Learning Model in the Sonographic Diagnosis of Uterine Adenomyosis.

International journal of environmental research and public health
BACKGROUND: This study aims to evaluate the diagnostic performance of Deep Learning (DL) machine for the detection of adenomyosis on uterine ultrasonographic images and compare it to intermediate ultrasound skilled trainees.

Development of a Wearable Ultrasound Transducer for Sensing Muscle Activities in Assistive Robotics Applications.

Biosensors
Robotic prostheses and powered exoskeletons are novel assistive robotic devices for modern medicine. Muscle activity sensing plays an important role in controlling assistive robotics devices. Most devices measure the surface electromyography (sEMG) s...

Current Advances in Computational Lung Ultrasound Imaging: A Review.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
In the field of biomedical imaging, ultrasonography has become common practice, and used as an important auxiliary diagnostic tool with unique advantages, such as being non-ionizing and often portable. This article reviews the state-of-the-art in med...

Ultrasound Signal Processing: From Models to Deep Learning.

Ultrasound in medicine & biology
Medical ultrasound imaging relies heavily on high-quality signal processing to provide reliable and interpretable image reconstructions. Conventionally, reconstruction algorithms have been derived from physical principles. These algorithms rely on as...

A Study on a Parameter Estimator for the Homodyned K Distribution Based on Table Search for Ultrasound Tissue Characterization.

Ultrasound in medicine & biology
OBJECTIVE: The homodyned K (HK) distribution is considered to be the most suitable distribution in the context of tissue characterization; therefore, the search for a rapid and reliable parameter estimator for HK distribution is important.

Degree of Accuracy With Which Deep Learning for Ultrasound Images Identifies Osteochondritis Dissecans of the Humeral Capitellum.

The American journal of sports medicine
BACKGROUND: Medical screening using ultrasonography (US) has been performed on young baseball players for early detection of osteochondritis dissecans (OCD) of the humeral capitellum. Deep learning (DL) and artificial intelligence (AI) techniques are...

FDE-net: Frequency-domain enhancement network using dynamic-scale dilated convolution for thyroid nodule segmentation.

Computers in biology and medicine
Thyroid nodules, a common disease of endocrine system, have a probability of nearly 10% to turn into malignant nodules and thus pose a serious threat to health. Automatic segmentation of thyroid nodules is of great importance for clinicopathological ...

Development of a Machine Learning Model for Sonographic Assessment of Gestational Age.

JAMA network open
IMPORTANCE: Fetal ultrasonography is essential for confirmation of gestational age (GA), and accurate GA assessment is important for providing appropriate care throughout pregnancy and for identifying complications, including fetal growth disorders. ...