Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks.

AI automation could 'revolutionize' Crohn's Disease severity CT assessments
Machine learning models could help create a more standardized, reproducible and efficient way of grading Crohn’s disease severity in the small bowel based on CT imaging.
New publicly available deep learning model for CT organ segmentation in children shows promise
The model was developed and validated specifically for liver, spleen and pancreas segmentation, and outperformed a publicly available segmentation model already in use.
New research offers reminder of why ChatGPT should not be used for second opinions
Although these tools have proven themselves valuable in numerous settings, they must be used with caution, especially by patients and nonradiologist providers who may be seeking clarification on imaging reports.
GPT-4 confidently struggles on radiology exam
Image-based questions were significantly more challenging for the large language model to answer, despite the latest version now being capable of accepting image prompts.
AI improves CT assessments, boosts care for real-world heart patients
Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.

MS findings may guide future neuroimaging biomarkers

Grey matter atrophy impacts localized brain regions that are functionally connected in patients with multiple sclerosis (MS), according to a new study published in Clinical Radiology. The results may serve as a framework for developing imaging biomarkers.

August 19, 2019

New technique pushes closer to real-time MRI brain imaging

A team of researchers backed by a division within the National Institutes of Health (NIH) has created a novel MRI technique that can image a thinking brain 60-times faster than traditional methods.

August 19, 2019

US global leader in publishing AI radiology studies

The United States published more AI-based radiology studies than any other country across the globe, according to a new analysis released Aug. 15 in the American Journal of Roentgenology.

August 16, 2019

AI trained on synthetic images makes accurate cancer diagnoses

A machine learning method trained on synthetic breast ultrasound elastography images accurately classified tumors when applied to real-world images, according to a new study published in the August issue of Computer Methods in Applied Mechanics and Engineering.

August 15, 2019

Repeated head hits cause brain damage regardless of concussions

A season of football can significantly damage a player’s brain, even if they did not experience a concussion. The results bolster evidence that suggests even repeated hits to the head can cause impactful brain damage.

August 14, 2019

MRI reveals ‘smoldering’ brain spots may indicate severe MS

“We hope these results will help test the effectiveness of new therapies for this form of MS and reduce the suffering patients experience,” said lead author of the study published in JAMA Neurology.

August 14, 2019

Neuroimaging shows e-devices may hamper understanding of complex concepts

A recent fMRI-based study found that learning via electronic devices such as smartphones or tablets can inhibit the brain’s ability to understand scientific texts, according to a recent study published by Scientific Reports.

August 13, 2019

ADHD medication can negatively impact child brain development

A commonly prescribed drug used to treat attention-deficit/hyperactivity disorder (ADHD) disproportionately affects the development of children’s brains compared to adults with ADHD, according to a new study published in Radiology.

August 13, 2019

Around the web

Cardiovascular Business

AI improves CT assessments, boosts care for real-world heart patients

Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.

Cardiovascular Business

AI predicts cardiovascular risk during CT scans—no invasive tests or contrast required

Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans.

Radiology Business

Google teams with Bayer to address radiologist burnout via AI

"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday.