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. 

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AI algorithm detects lung nodules with 95% accuracy

Researchers at the University of Central Florida’s Center for Research in Computer Vision have created an artificial intelligence (AI) algorithm that can detect specks of lung cancer in CT scans with 95 percent accuracy.

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VR tool could enhance medical imaging segmentation, error correction

Virtual Brain Segmenter (VBS), which automatically processes medical imaging data such as MRIs through segmentation, could increase the efficiency of brain scan analysis, according to a USC news release from Aug. 21.

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Iron-based MRI contrast performs twice as well as gadolinium

Nanoscientists at Rice University in Houston have created a method to pack iron into nanoparticles to create MRI contrast agents that outperform gadolinium-based agents, according to research published in ACS Nano.

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AI software detects lung cancer on CT scans with 95% accuracy

Engineers at the University of Central Florida's Center for Research in Computer Vision have developed an artificial intelligence (AI)-based system that can detect lung cancer on CT scans with 95 percent accuracy, according to a UCF news release.

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Hybrid method may improve dataset quality, quantity for deep learning

A hybrid technique combining natural language processing (NLP) and IBM Watson can accurately label free-text pathology reports, according to a new Journal of Digital Imaging study. The method may improve the quality and quantity of large-scale datasets for deep learning.

VR headset lets families, caregivers empathize with Alzheimer’s

A Chicago-based company believes its virtual-reality (VR) training program can help caregivers and families empathize with Alzheimer’s patients, according to a Chicago Magazine story.

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Facebook, NYU collaborate to make MRI faster with AI

The project could produce MRI images up to 10 times faster and make MRI technology more widely available. These accelerated MRIs could also fill the role of x-ray and CT machines by making imaging quicker and safer, according to a Facebook news release.

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Intel, Philips work together to test how AI can speed up imaging analysis

Intel and Philips announced that they have joined forces to work on artificial intelligence (AI) by using Intel’s Xeon Scalable processors and OpenVINO toolkit to test two use cases for deep learning inference models.

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