AI

Addressing upgrades of traditional infrastructure used in everyday radiology practice may be a more practical use of resources than investment in artificial intelligence (AI) technology that is still evolving.

AIR Recon DL, a deep learning-based image reconstruction software, will now be available with 3D sequences as well as PROPELLER motion-insensitive sequences on magnetic resonance imaging (MRI) scanners from GE Healthcare.

Catch up on the top AI-related radiology content of the past month.

Given the influx of artificial intelligence (AI)-powered tools in health care, this author examines the potential intersection of this technology and ultrasound examination in obstetrics and gynecologic (OB/GYN) care

New research reveals that an emerging deep learning tool had comparable sensitivity and specificity to radiologist assessment of contrast-enhanced computed tomography (CT) scans for pancreatic cancer, and a 74.7 percent sensitivity rate for tumors smaller than 2 cm.

Assessing high-resolution computed tomography (CT) scans of the wrist, CurveBeam AI’s OssView software reportedly enables clinicians to ascertain bone fragility and fracture risk for women over the age of 70.

Catch up on the top radiology content of the past week.

Offering uniform high-resolution images through a combination of beamforming and enhanced image processing, the new ultrasound platform reportedly has an array of diagnostic features ranging from cardiovascular applications to breast lesion assessment.

Examining imaging data of patients from multiple countries, researchers found that a deep learning system demonstrated higher sensitivity and non-inferior specificity for detecting active tuberculosis on chest radiographs in comparison to nine radiologist reviewers.

A little positivity and praise towards others can go a long way for how you assess and treat yourself, too.

Researchers suggest that an artificial intelligence (AI)-powered risk stratification tool for lung nodules identified on computed tomography (CT) scans may identify likely malignancies more than one year prior to definitive diagnosis.

Catch up on the top radiology content of the past week.

Researchers found that stand-alone use of an artificial intelligence (AI) model led to a 24.9 percent increase in sensitivity for diagnosing pulmonary nodules and a 21.4 percent increase in sensitivity for diagnosing pneumonia.

The automated measurement of heart ventricle diameters and detection of potential dilation in the right ventricle may facilitate quicker intervention in cases of pulmonary embolism.

In comparison to initial sonographer assessment of echocardiograms, cardiologists are over 10 percent less likely to change initial artificial intelligence (AI) assessment of left ventricular ejection fraction (LVEF), according to new research recently presented at the European Society of Cardiology Congress in Barcelona, Spain.

Catch up on the top AI-related radiology content of the past month.

The Maestro Brain Model reportedly provides automated identification, quantification and labeling of brain structures on magnetic resonance imaging (MRI).

Emerging research suggests the machine learning-based DiaBeats algorithm could facilitate early detection of prediabetes or diabetes.

The ProstatID, an adjunctive artificial intelligence software that radiologists can utilize with traditional magnetic resonance imaging (MRI), reportedly measures prostate gland volume, and suggests PI-RADS scoring of suspicious lesions.

Catch up on the top radiology content of the past week.

Researchers discuss key parameters for the assessment, implementation and post-implementation monitoring of emerging artificial intelligence (AI) tools in radiology practices large and small.

The Definium 656 HD fixed X-ray system reportedly features enhanced, artificial intelligence (AI)-driven image processing, facilitates radiology workflows, and reduces patient positioning time.

Preliminary research revealed an area under the curve (AUC) of 85 percent for an artificial intelligence (AI) algorithm in diagnosing COVID-19 on initial chest X-rays in comparison to a consensus 71 percent AUC for five radiologists.

Viz.ai said the Viz Subdural Hematoma (SDH) artificial intelligence (AI) algorithm provides automatic detection of acute and chronic subdural hemorrhages, facilitating timely triage and treatment of patients.

Catch up on the top radiology content of the past week.