Radiology

Deep learning radiomics on shear wave elastography and b-mode ultrasound videos of diaphragm for weaning outcome prediction.

PURPOSE: We proposed an automatic method based on deep learning radiomics (DLR) on shear wave elasto...

Intraoperative molecular diagnosis of glioma through combination of radiofrequency signals from ultrasound and deep learning.

Machine learning and deep learning for brain tumor MRI image segmentation.

Brain tumors are often fatal. Therefore, accurate brain tumor image segmentation is critical for the...

Deep learning algorithm for predicting preterm birth in the case of threatened preterm labor admissions using transvaginal ultrasound.

PURPOSE: Preterm birth presents a major challenge in perinatal care, and predicting preterm birth re...

A 5G-based telerobotic ultrasound system provides qualified abdominal ultrasound services for patients on a rural island: a prospective and comparative study of 401 patients.

PURPOSE: To explore the feasibility of a 5G-based telerobotic ultrasound (US) system for providing q...

A deep learning approach to the automatic detection of alignment errors in cryo-electron tomographic reconstructions.

Electron tomography is an imaging technique that allows for the elucidation of three-dimensional str...

Application of a deep learning algorithm for three-dimensional T1-weighted gradient-echo imaging of gadoxetic acid-enhanced MRI in patients at a high risk of hepatocellular carcinoma.

PURPOSE: To evaluate the efficacy of a vendor-specific deep learning reconstruction algorithm (DLRA)...

Feasibility of artificial intelligence its current status, clinical applications, and future direction in cardiovascular disease.

In routine clinical practice, the diagnosis and treatment of cardiovascular disease (CVD) rely on da...

Noninvasive diagnostic imaging for endometriosis part 1: a systematic review of recent developments in ultrasound, combination imaging, and artificial intelligence.

Endometriosis affects 1 in 9 women and those assigned female at birth. However, it takes 6.4 years t...

Improving Valvular Pathologies and Ventricular Dysfunction Diagnostic Efficiency Using Combined Auscultation and Electrocardiography Data: A Multimodal AI Approach.

Simple sensor-based procedures, including auscultation and electrocardiography (ECG), can facilitate...

Review of Deep Learning Approaches for Interleaved Photoacoustic and Ultrasound (PAUS) Imaging.

Photoacoustic (PA) imaging provides optical contrast at relatively large depths within the human bod...

Ultrafast Cardiac Imaging Using Deep Learning for Speckle-Tracking Echocardiography.

High-quality ultrafast ultrasound imaging is based on coherent compounding from multiple transmissio...

Diagnosis of COVID-19 with simultaneous accurate prediction of cardiac abnormalities from chest computed tomographic images.

COVID-19 has potential consequences on the pulmonary and cardiovascular health of millions of infect...

Advances in Clinical Imaging of Vascular Inflammation: A State-of-the-Art Review.

Vascular inflammation is a major contributor to cardiovascular disease, particularly atherosclerotic...

Current applications of algorithmic artificial intelligence in interventional radiology: A review of the literature.

Artificial intelligence is a rapidly evolving area of technology whose integration into healthcare d...

Convolutional neural network-assisted diagnosis of midpalatal suture maturation stage in cone-beam computed tomography.

OBJECTIVES: The selection of treatment for maxillary expansion is closely related to the calcificati...

Identification of IDH and TERTp mutations using dynamic susceptibility contrast MRI with deep learning in 162 gliomas.

PURPOSE: Isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase gene promoter (TERTp) m...

Automated detection and segmentation of pleural effusion on ultrasound images using an Attention U-net.

BACKGROUND: Ultrasonic for detecting and evaluating pleural effusion is an essential part of the Ext...

The endorsement of general and artificial intelligence reporting guidelines in radiological journals: a meta-research study.

BACKGROUND: Complete reporting is essential for clinical research. However, the endorsement of repor...

AI approach to biventricular function assessment in cine-MRI: an ultra-small training dataset and multivendor study.

. It was a great challenge to train an excellent and generalized model on an ultra-small data set co...

Retracted: Ultrasound Lung Image under Artificial Intelligence Algorithm in Diagnosis of Neonatal Respiratory Distress Syndrome.

[This retracts the article DOI: 10.1155/2022/1817341.].