AIMC Topic: Ultrasonography

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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...

An Automated Deep Learning Model for the Cerebellum Segmentation from Fetal Brain Images.

BioMed research international
Cerebellum measures taken from routinely obtained ultrasound (US) images have been frequently employed to determine gestational age and identify developing central nervous system's anatomical abnormalities. Standardized cerebellar assessments from la...

Application of a Tele-Ultrasound Robot During COVID-19 Pandemic: A Feasibility Study.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVE: To investigate the accuracy of ultrasonic diagnosis using the tele-ultrasound robot in Leishen Shan Hospital.

Real-time denoising of ultrasound images based on deep learning.

Medical & biological engineering & computing
Ultrasound images are widespread in medical diagnosis for muscle-skeletal, cardiac, and obstetrical diseases, due to the efficiency and non-invasiveness of the acquisition methodology. However, ultrasound acquisition introduces noise in the signal, w...

Deep Learning Algorithm-Based Ultrasound Image Information in Diagnosis and Treatment of Pernicious Placenta Previa.

Computational and mathematical methods in medicine
This study was to explore the value of the deep dictionary learning algorithm in constructing a B ultrasound scoring system and exploring its application in the clinical diagnosis and treatment of pernicious placenta previa (PPP). 60 patients with PP...