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. 

Thumbnail

Literature review suggests most fMRI findings have been unreliable at best

A new analysis of the literature on fMRI suggests that a shortcoming in the most popular software systems used to evaluate the imaging data—SPM, FSL and AFNI—may have caused all three to produce false positive findings at a 70 percent clip from 1992 to 2015. 

There soon may be an imaging system under your skin

Engineers at the University of Stuttgart in Germany have designed an imaging system so tiny that it can be sent straight into human tissue.

Thumbnail

When teaching radiology, don’t forget to embrace the unknown

Most articles in today’s radiology journals focus on specific case studies or problems facing the industry. A recent editorial published in the Journal of the American College of Radiology, however, really caught my eye by taking a deeper, more philosophical approach.

Thumbnail

The U.S. healthcare system is damaging to environment. So now what?

Here’s a not-so-fun thought: our healthcare system is having a bad effect on the environment. It’s having a really bad effect, actually. 

Intermountain docs image, model and save patient’s kidney

Using CT scans to create a 3-D printout of a patient’s kidney for presurgical planning, a urologist and a radiologist at Intermountain Healthcare in Utah have led a care team in removing a complicated tumor while preserving the actual kidney.

Gray matter differences imaged in diabetic teens

Prior research has established that teenagers with type 2 diabetes have different gray-matter volumes and poorer cognitive function than their nondiabetic peers. A new MRI-based study at Cincinnati Children's Hospital Medical Center has imaged the particular regions in which the differences occur. 

Thumbnail

Diffusion MR proves adept at predicting concussion outcomes

Diffusion tensor MRI can be used to separate concussion patients who are likely to fully recover within a year from those who are likely to suffer longer-term effects, pointing to the most appropriate treatment pathways for each. 

‘Hyperscanning’ shows sex differences in the brains of pairs asked to cooperate with one another

Forgoing fMRI in favor of “hyperscanning” with near-infrared spectroscopy, or NIRS, Stanford researchers have uncovered intriguing differences in brain activity between males and females who have been asked to cooperate. 

Around the web

RBMA President Peter Moffatt discusses declining reimbursement rates, recruiting challenges and the role of artificial intelligence in transforming the industry.

Deepak Bhatt, MD, director of the Mount Sinai Fuster Heart Hospital and principal investigator of the TRANSFORM trial, explains an emerging technique for cardiac screening: combining coronary CT angiography with artificial intelligence for plaque analysis to create an approach similar to mammography.

A total of 16 cardiology practices from 12 states settled with the DOJ to resolve allegations they overbilled Medicare for imaging agents used to diagnose cardiovascular disease.