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Artificial Intelligence: Page 100
The great enabler: Artificial intelligence in radiology
By
Steve Holloway
Much has already been debated over the effect of artificial intelligence (AI) for radiology, and now the first products have started to enter the market. AI will not replace radiologists, but enable them, according to market analyst Stephen Holloway.
March 23, 2017
CAD beats readers for subsolid lung nodules
By
Eric Barnes
VIENNA - A computer-aided detection (CAD) scheme outperformed experienced human readers in detecting subsolid nodules as well as cancers in data from more than 2,000 lung cancer screening subjects, researchers reported on Thursday at ECR 2017.
March 2, 2017
Spanish group seeks to integrate CAD, PACS
By
Erik L. Ridley
Computer-aided detection (CAD) software and PACS software may not always be integrated in the most user-friendly fashion. A Spanish research group hopes to change that with a new software platform that will make it easier for all hospitals in the region of Galicia to expand their use of CAD.
February 22, 2017
Alzheimer's CAD uses deep networks to boost accuracy
By
Eric Barnes
Spanish researchers have built a technique for the early diagnosis of Alzheimer's disease based on the use of a deep-learning algorithm. The method replaces visual inspection of MRI and PET data with comprehensive image analysis of affected brain tissues that exploits their 3D nature.
February 22, 2017
Machine learning in radiology targets efficiency
By
Simon Harris
While artificial intelligence is unlikely to replace radiologists any time soon, a new breed of software applications based on machine learning is poised to take on many of their tedious, repetitive, and time-consuming tasks -- improving productivity and freeing up more time.
February 5, 2017
Prostate CAD boosts detection for most readers
By
Eric Barnes
CHICAGO - MRI-based computer-aided detection (CAD) can improve detection sensitivity for prostate cancer for most readers, while reducing reading time fourfold, according to a 29 November presentation at RSNA 2016.
November 30, 2016
CAD with low-dose CT shows promise in lung
By
Frances Rylands-Monk
New Swiss research shows that adding computer-aided detection (CAD) in ultralow-dose CT significantly improves sensitivity for detecting solid pulmonary nodules. This may be a crucial step in the early detection of lung cancer and lead to better patient outcomes.
November 6, 2016
Texture classification eases lung CT analysis
By
Ian Randall
Dutch researchers have developed a semiautomatic method for classifying abnormal lung textures that reduces the time taken to analyze thoracic CT scans. They found the interactive labeling protocol is more efficient to use than a fully automated alternative.
September 4, 2016
How low can CT radiation dose go for lung screening?
By
Eric Barnes
We're making progress in the race to reduce radiation dose for CT lung cancer screening to ever-lower levels. But as dose drops, image noise grows. Fortunately, researchers are refining image processing techniques that can improve image quality while driving CT dose down to the level of a chest x-ray.
August 17, 2016
New neural network outperforms CAD for mammography
By
Eric Barnes
A convolutional neural network trained on a large dataset of mammographic lesions outperformed a conventional mammography computer-aided detection (CAD) scheme, according to a new Dutch study published this month. These networks can be fine-tuned based on radiologists' knowledge.
August 15, 2016
X-ray software delivers 4 bone health measures
By
Eric Barnes
New software that analyzes bone age and health from hand radiography has revealed fresh information about changes in bone density and osteoporosis over a lifetime, according to a German-Danish research group.
May 15, 2016
Global medical image analysis market to top $3B by 2020
By
AuntMinnieEurope.com staff writers
The global market for medical image analysis software is expected to reach $3.14 billion by 2020, according to research firm MarketsandMarkets.
April 24, 2016
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