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Ultrasonography

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Automated Real-Time Detection of Lung Sliding Using Artificial Intelligence: A Prospective Diagnostic Accuracy Study.

Chest
BACKGROUND: Rapid evaluation for pneumothorax is a common clinical priority. Although lung ultrasound (LUS) often is used to assess for pneumothorax, its diagnostic accuracy varies based on patient and provider factors. To enhance the performance of ...

The Promise of Artificial Intelligence-Assisted Point-of-Care Ultrasonography in Perioperative Care.

Journal of cardiothoracic and vascular anesthesia
The role of point-of-care ultrasonography in the perioperative setting has expanded rapidly over recent years. Revolutionizing this technology further is integrating artificial intelligence to assist clinicians in optimizing images, identifying anoma...

Phase Aberration Correction for In Vivo Ultrasound Localization Microscopy Using a Spatiotemporal Complex-Valued Neural Network.

IEEE transactions on medical imaging
Ultrasound Localization Microscopy (ULM) can map microvessels at a resolution of a few micrometers ( [Formula: see text]). Transcranial ULM remains challenging in presence of aberrations caused by the skull, which lead to localization errors. Herein,...

Ultrasound tomography enhancement by signal feature extraction with modular machine learning method.

PloS one
Robust and reliable diagnostic methods are desired in various types of industries. This article presents a novel approach to object detection in industrial or general ultrasound tomography. The key idea is to analyze the time-dependent ultrasonic sig...

Deep learning for real-time multi-class segmentation of artefacts in lung ultrasound.

Ultrasonics
Lung ultrasound (LUS) has emerged as a safe and cost-effective modality for assessing lung health, particularly during the COVID-19 pandemic. However, interpreting LUS images remains challenging due to its reliance on artefacts, leading to operator v...

Deep learning diagnostic performance and visual insights in differentiating benign and malignant thyroid nodules on ultrasound images.

Experimental biology and medicine (Maywood, N.J.)
This study aims to construct and evaluate a deep learning model, utilizing ultrasound images, to accurately differentiate benign and malignant thyroid nodules. The objective includes visualizing the model's process for interpretability and comparing ...

Deep learning-based osteochondritis dissecans detection in ultrasound images with humeral capitellum localization.

International journal of computer assisted radiology and surgery
PURPOSE: Osteochondritis dissecans (OCD) of the humeral capitellum is a common cause of elbow disorders, particularly among young throwing athletes. Conservative treatment is the preferred treatment for managing OCD, and early intervention significan...

Beyond the Echo: The Evolution and Revolution of Ultrasound in Anesthesia.

Anesthesia and analgesia
This article explores the evolving role of ultrasound technology in anesthesia. Ultrasound emerged decades ago, offering clinicians noninvasive, economical, radiation-free, and real-time imaging capabilities. It might seem that such an old technology...

Analysis of neural networks for routine classification of sixteen ultrasound upper abdominal cross sections.

Abdominal radiology (New York)
PURPOSE: Abdominal ultrasound screening requires the capture of multiple standardized plane views as per clinical guidelines. Currently, the extent of adherence to such guidelines is dependent entirely on the skills of the sonographer. The use of neu...