AI Medical Compendium Topic:
Ultrasonography

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Convolutional Neural Network for Breast and Thyroid Nodules Diagnosis in Ultrasound Imaging.

BioMed research international
OBJECTIVE: The incidence of superficial organ diseases has increased rapidly in recent years. New methods such as computer-aided diagnosis (CAD) are widely used to improve diagnostic efficiency. Convolutional neural networks (CNNs) are one of the mos...

Bimodal Automated Carotid Ultrasound Segmentation Using Geometrically Constrained Deep Neural Networks.

IEEE journal of biomedical and health informatics
For asymptomatic patients suffering from carotid stenosis, the assessment of plaque morphology is an important clinical task which allows monitoring of the risk of plaque rupture and future incidents of stroke. Ultrasound Imaging provides a safe and ...

Objective Analysis of Neck Muscle Boundaries for Cervical Dystonia Using Ultrasound Imaging and Deep Learning.

IEEE journal of biomedical and health informatics
OBJECTIVE: To provide objective visualization and pattern analysis of neck muscle boundaries to inform and monitor treatment of cervical dystonia.

Contrast-Enhanced Ultrasound Quantification: From Kinetic Modeling to Machine Learning.

Ultrasound in medicine & biology
Ultrasound contrast agents (UCAs) have opened up immense diagnostic possibilities by combined use of indicator dilution principles and dynamic contrast-enhanced ultrasound (DCE-US) imaging. UCAs are microbubbles encapsulated in a biocompatible shell....

Deep Learning-Based Super-resolution Ultrasound Speckle Tracking Velocimetry.

Ultrasound in medicine & biology
Deep ultrasound localization microscopy (deep-ULM) allows sub-wavelength resolution imaging with deep learning. However, the injection of contrast agents (CAs) in deep-ULM is debatable because of their potential risk. In this study, we propose a deep...

Accurate prediction of responses to transarterial chemoembolization for patients with hepatocellular carcinoma by using artificial intelligence in contrast-enhanced ultrasound.

European radiology
OBJECTIVES: We aimed to establish and validate an artificial intelligence-based radiomics strategy for predicting personalized responses of hepatocellular carcinoma (HCC) to first transarterial chemoembolization (TACE) session by quantitatively analy...

Localization of common carotid artery transverse section in B-mode ultrasound images using faster RCNN: a deep learning approach.

Medical & biological engineering & computing
Cardiologists can acquire important information related to patients' cardiac health using carotid artery stiffness, its lumen diameter (LD), and its carotid intima-media thickness (cIMT). The sonographers primarily concern about the location of the a...

Semantic segmentation with DenseNets for carotid artery ultrasound plaque segmentation and CIMT estimation.

Artificial intelligence in medicine
BACKGROUND AND OBJECTIVE: The measurement of carotid intima media thickness (CIMT) in ultrasound images can be used to detect the presence of atherosclerotic plaques. Usually, the CIMT estimation strategy is semi-automatic, since it requires: (1) a m...

A novel transcranial ultrasound imaging method with diverging wave transmission and deep learning approach.

Computer methods and programs in biomedicine
Real time brain transcranial ultrasound imaging is extremely intriguing because of its numerous applications. However, the skull causes phase distortion and amplitude attenuation of ultrasound signals due to its density: the speed of sound is signifi...

Deep Convolutional Neural Network-Based Automatic Classification of Neonatal Hip Ultrasound Images: A Novel Data Augmentation Approach with Speckle Noise Reduction.

Ultrasound in medicine & biology
Neonatal hip ultrasound imaging has been widely used for a few decades in the diagnosis of developmental dysplasia of the hip (DDH). Graf's method of hip ultrasonography is still the most reproducible because of its classification system; yet, the re...