Medical Imaging

Physicians utilize medical imaging to see inside the body to diagnose and treat patients. This includes computed tomography (CT), magnetic resonance imaging (MRI), X-ray, ultrasound, fluoroscopy, angiography,  and the nuclear imaging modalities of PET and SPECT. 

As artificial intelligence (AI) adoption expands in radiology, there is growing concern that AI algorithms needs to undergo quality assurance (QA) reviews. How to validate radiology AI? How can you validate medical imaging AI?

Better together: Radiology researchers see improved results when combining AI models

Ensemble learning—the combination of multiple AI models into a single model with a single purpose—can lead to better overall results, according to new research published in Radiology: Artificial Intelligence.

November 21, 2019

Lunit’s AI solution for x-ray analysis gains CE certification

Lunit, a medical software company based out of South Korea, has gained CE certification for its newest chest x-ray analysis solution, Lunit INSIGHT CXR.

November 20, 2019
Artificial intelligence (AI) has been one of the biggest stories in healthcare for years, but many clinicians still remain unsure about how, exactly, they should be using AI to help their patients. A new analysis in European Heart Journal explored that exact issue, providing cardiology professionals with a step-by-step breakdown of how to get the most out of this potentially game-changing technology.

Q&A: George Shih previews RSNA 2019, discusses AI’s impact on radiology

RSNA 2019 in Chicago is just days away, and the continued evolution of AI in radiology promises to be one of the hottest topics of the entire conference.

November 19, 2019

Imaging data help AI models predict lymph node metastasis

Deep learning models can be trained to predict lymph node metastasis in breast cancer patients, according to new findings published in Radiology.

November 19, 2019
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How AI-powered triage impacts radiology, radiologists

AI can provide significant value to radiologists by sending urgent imaging studies to the top of their worklists, according to a new analysis published in Academic Radiology.

November 18, 2019

Google canceled publication of chest x-ray dataset due to privacy concerns

Google was hoping to release a massive dataset of chest x-rays to the public in 2017, but had to cancel at the last minute after receiving an urgent call from the National Institutes of Health (NIH).   

November 15, 2019
As artificial intelligence (AI) adoption expands in radiology, there is growing concern that AI algorithms needs to undergo quality assurance (QA) reviews. How to validate radiology AI? How can you validate medical imaging AI?

AI system for ultrasound-based heart scans receives FDA approval

Ultromics, a U.K.-based healthcare technology company, has gained FDA clearance for its new AI-powered image analysis solution.

November 14, 2019
Michael Walter update

3 can't-miss AI sessions at RSNA 2019

RSNA 2019, the world’s largest radiology conference, kicks off at Chicago’s McCormick Place on Sunday, Dec. 1. This year's show promises to include more AI content than ever before.

November 13, 2019

Around the web

U.S. health systems are increasingly leveraging digital health to conduct their operations, but how health systems are using digital health in their strategies can vary widely.

When human counselors are unavailable to provide work-based wellness coaching, robots can substitute—as long as the workers are comfortable with emerging technologies and the machines aren’t overly humanlike.

A vendor that supplies EHR software to public health agencies is partnering with a health-tech startup in the cloud-communications space to equip state and local governments for managing their response to the COVID-19 crisis.

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