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Artificial Intelligence

Image: Researchers are working to develop the application of AI in medical imaging diagnostics (Photo courtesy of Digital Health).

Fujifilm and IU School of Medicine to Study AI in Diagnostic Imaging

Fujifilm Corporation has entered into a joint research agreement with Indiana University School of Medicine to develop the application of artificial intelligence (AI) in medical imaging diagnostic support systems. More...
12 Sep 2018
Image: A new study claims computer-aided diagnosis can help identify cancerous polyps (Photo courtesy of Yuichi Mori/ SUHY).

AI Reliably Identifies Diminutive Polyps During Colonoscopy

Real-time computer-aided diagnosis (CAD) may help endoscopists distinguish between small neoplastic and benign polyps during colonoscopy, claims a new study. More...
10 Sep 2018
Image: Assistant Professor Ulas Bagci leads the group of engineers at the University of Central Florida that have taught a computer how to detect tiny specks of lung cancer in CT scans, which radiologists often have a difficult time identifying. The artificial intelligence system is about 95 percent accurate, compared to 65 percent when done by human eyes, the team said (Photo courtesy of the University of Central Florida, Karen Norum).

AI System Accurately Detects Lung Cancer in CT Scans

Engineers from the University of Central Florida's Computer Vision Research Center have developed an artificial intelligence (AI) system which can detect tiny specks of lung cancer in CT scans. Radiologists find it difficult to identify such tiny tumors and have an accuracy of 65%, while the AI system has an accuracy of about 95%, according to the engineers. More...
05 Sep 2018
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: 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
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 The Artificial Intelligence channel of HospiMedica keeps the reader informed about the latest news in AI-based clinical decision making, Medical knowledge engineering, Intelligent medical information systems and additional related fields.
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