AI Medical Compendium Topic:
Ultrasonography

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Using deep learning for ultrasound images to diagnose carpal tunnel syndrome with high accuracy.

Ultrasound in medicine & biology
Recently, deep learning (DL) algorithms have been adapted for the diagnosis of medical images. The purpose of this study was to detect image features using DL without measuring median nerve cross-sectional area (CSA) in ultrasonography (US) images of...

Successful Use of a 5G-Based Robot-Assisted Remote Ultrasound System in a Care Center for Disabled Patients in Rural China.

Frontiers in public health
BACKGROUND: Disability has become a global population health challenge. Due to difficulties in self-care or independent living, patients with disability mainly live in community-based care centers or institutions for long-term care. Nonetheless, thes...

Machine learning-enabled quantitative ultrasound techniques for tissue differentiation.

Journal of medical ultrasonics (2001)
PURPOSE: Quantitative ultrasound (QUS) infers properties about tissue microstructure from backscattered radio-frequency ultrasound data. This paper describes how to implement the most practical QUS parameters using an ultrasound research system for t...

Robot-assisted vs ultrasonography-guided transversus abdominis plane (TAP) block vs local anaesthesia in urology: results of the UROTAP randomized trial.

BJU international
OBJECTIVES: To prospectively analyse robotically administered transperitoneal transversus abdominis plane (robot-assisted transversus abdominis plane [RTAP]) compared with both ultrasonography-guided transversus abdominis plane (UTAP) and local anaes...

Performance of a generative adversarial network using ultrasound images to stage liver fibrosis and predict cirrhosis based on a deep-learning radiomics nomogram.

Clinical radiology
AIM: To investigate the performance of a generative adversarial network (GAN) model for staging liver fibrosis and its radiomics-based nomogram for predicting cirrhosis.

SAFNet: A deep spatial attention network with classifier fusion for breast cancer detection.

Computers in biology and medicine
Breast cancer is a top dangerous killer for women. An accurate early diagnosis of breast cancer is the primary step for treatment. A novel breast cancer detection model called SAFNet is proposed based on ultrasound images and deep learning. We employ...

Deep-fUS: A Deep Learning Platform for Functional Ultrasound Imaging of the Brain Using Sparse Data.

IEEE transactions on medical imaging
Functional ultrasound (fUS) is a rapidly emerging modality that enables whole-brain imaging of neural activity in awake and mobile rodents. To achieve sufficient blood flow sensitivity in the brain microvasculature, fUS relies on long ultrasound data...

Deep learning to diagnose Hashimoto's thyroiditis from sonographic images.

Nature communications
Hashimoto's thyroiditis (HT) is the main cause of hypothyroidism. We develop a deep learning model called HTNet for diagnosis of HT by training on 106,513 thyroid ultrasound images from 17,934 patients and test its performance on 5051 patients from 2...

Application of Recurrent Neural Network Algorithm in Intelligent Detection of Clinical Ultrasound Images of Human Lungs.

Computational intelligence and neuroscience
Lung ultrasound has great application value in the differential diagnosis of pulmonary exudative lesions. It has good sensitivity and specificity for the diagnosis of various pulmonary diseases in neonates and children. It is believed that it can rep...

Deep learning for emergency ascites diagnosis using ultrasonography images.

Journal of applied clinical medical physics
PURPOSE: The detection of abdominal free fluid or hemoperitoneum can provide critical information for clinical diagnosis and treatment, particularly in emergencies. This study investigates the use of deep learning (DL) for identifying peritoneal free...