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. 

Advanced imaging, genomic analysis may change the way we treat cancer patients

"This study is a bridge between genetic sequencing, single-cell analysis and high-resolution medical imaging," researchers said of their study published in PLOS One.

January 31, 2020
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What MRI and 100 years of horror movies can teach us about our brains

Finnish researchers had volunteers watch two of the century's scariest horror films inside an MRI machine while recording their brain activity, sharing their findings this month in NeuroImage.

January 28, 2020

Sex, money and food: fMRI reveals how the brain processes rewards

These three items activate similar brain locations, according to the study published this month in Brain and Imaging Behavior, but do so in very different ways.

January 24, 2020

AI reads images in milliseconds—bringing low-cost malaria detection to resource-strapped areas

The deep learning model can identify parasites that cause the disease in blood sample images as accurately as human experts, but in a fraction of the time, researchers wrote in the Journal of Digital Imaging.

 

January 24, 2020

Experts urge radiology to be more cognizant of image resolution’s impact on AI

Two researchers found that using certain pixel dimensions helped tailor algorithms to detect specific abnormalities, and pushed radiology to keep this in mind when using such approaches.

January 23, 2020
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Explainable deep learning predicts pulmonary blood flow from x-rays

Japan-based researchers believe the algorithm can illuminate "hidden" information contained in imaging exams, and help radiologists in their clinical decision-making.

January 22, 2020
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?

Radiology technologists ‘poised’ to embrace, supervise upcoming AI era

That's according to a recent white paper published by the American Society of Radiologic Technologists.

January 20, 2020

Virtual reality can take the stress out of breast cancer treatment

Women who wore a VR headset during chemotherapy reported less anxiety and a better mood following their appointment.

January 20, 2020

Around the web

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.

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

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

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