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Image: The American College of Radiology Data Science Institute has started releasing its first AI use cases in the ACR DSI TOUCH-AI library for generating feedback (Photo courtesy of the ACR).

American College of Radiology Releases Initial Use Cases in AI Library

The American College of Radiology Data Science Institute has started releasing its first artificial intelligence (AI) use cases in the ACR DSI TOUCH-AI library for generating feedback ahead of the projected release of all of the use cases in the fall. More...
03 Sep 2018
Image: The global radiation dose management market is projected to reach USD 1.36 billion by 2026 (Photo courtesy of Transparency Market Research).

Global Radiation Dose Management Market to Reach USD 1.3 Billion by 2026

The global radiation dose management market was valued at USD 143.2 million in 2017 and is projected to register a CAGR of 26.7% from 2018 to 2026 to reach USD 1.36 billion in 2026. More...
03 Sep 2018
Radcal
Image: All-optical ultrasound imager. This prototype is the first all-optical ultrasound imager to demonstrate video-rate, real-time 2D imaging of biological tissue. The achievement is an important step toward making all-optical ultrasound practical for routine clinical use, where it could offer significant advantages over current imaging technology (Photo courtesy of Erwin J. Alles, University College London).

New All-Optical System Could Revolutionize Image-Guided Interventions

A new ultrasound system that uses optical, instead of electronic components, could improve performance while providing doctors with significantly more flexibility in the way they use ultrasound to diagnose and treat medical problems. For the first time, researchers have demonstrated the use of an all-optical ultrasound imager for video-rate, real-time 2D imaging of biological tissue, marking a significant step towards making all-optical ultrasound practical for routine clinical use. Since all-optical ultrasound systems do not require any electronic components in the imaging probe, they could be safely used at the same time as magnetic resonance imaging (MRI) scanners. This can provide doctors with a more comprehensive picture of the tissues around an area of interest, such as a tumor or blood vessel, according to a recent paper published in the Optical Society (OSA) journal Biomedical Optics Express. More...
29 Aug 2018
Image: A brain scan showing vascular dementia (Photo courtesy of Radiopaedia).

Machine-Learning Scans Accurately Predict Undiagnosed Dementia

Researchers from the University of Plymouth have developed a new machine-learning model that scanned routinely collected National Health Service (NHS) data in a study and predicted undiagnosed dementia in primary care with high accuracy. More...
29 Aug 2018
Image: MR images reconstructed from the same data with conventional approaches, at left, and AUTOMAP, at right (Photo courtesy of Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital).

AI-Based Approach to Image Reconstruction Provides Faster and Clearer MRI Scans

Researchers from the Massachusetts General Hospital (MGH) Martinos Center for Biomedical Imaging and Harvard University have used artificial intelligence to develop a new type of medical imaging technology called AUTOMAP, which produces higher-quality images from less information. This cuts down the amount of radiation from CT and PET scans, thus reducing the duration of an MRI scan. The research was funded by the National Institute for Biomedical Imaging and Bioengineering. More...
28 Aug 2018
Image: New research claims to be able to predict a person’s intelligence by using an algorithm and fMRI scans (Photo courtesy of Pixabay).

New Algorithm Predicts IQ Scores Using fMRI Brain Scans

A team of researchers from the California Institute of Technology, Cedars-Sinai Medical Center, and the University of Salerno have developed a machine-learning algorithm that can predict a person's intelligence by analyzing functional magnetic resonance imaging (fMRI) scans of their resting state brain activity. More...
28 Aug 2018

Intel and Philips Partner to Speed Up Imaging Analysis Using AI

Intel Corporation and Royal Philips have tested two healthcare use cases for deep learning inference models: one on X-rays of bones for bone-age-prediction modeling and the other on CT scans of lungs for lung segmentation. In these tests, which were conducted using Intel Xeon Scalable processors and the OpenVINO toolkit, the researchers achieved a speed improvement of 188 times for the bone-age-prediction model and 38 times for the lung-segmentation model over the baseline measurements. These tests show that healthcare organizations can implement artificial intelligence (AI) workloads without expensive hardware investments. More...
22 Aug 2018
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