Carestream accelerates delivery of AI features that help improve patient outcomes and patient care. Table of contents AI's role in improving clinical outcomes AI's role in improving the human experience Accelerating delivery of AI applications for radiology There are numerous technologies and technical terms related to artificial intelligence (AI) that
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Study results demonstrate Smart Noise Cancellation delivers significant improvement in dose efficiency. Table of contents Radiation dose reduction study Reader study results Study conclusions Best practice in medical X-ray imaging employs the principle of ALARA – “as low as reasonably achievable” – for radiation dose management. A consequence of this
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Smart DR Workflow helps improve image quality and consistency, and speed patient throughput. Applications for Artificial Intelligence (AI) in radiology are increasing, especially in workflow where they can help streamline exam efficiency and provide more consistent outcomes. Carestream’s software powered by Eclipse uses AI to optimize
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Carestream applies Artificial Intelligence to improve medical image quality. In some ways, the path to improving X-ray image quality seems pretty straightforward. There are three fundamental components of image quality: noise, sharpness, and contrast. The complexity comes from the fact that the sharpness and the noise
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AI delivers enhanced imaging and improved workflow for medical imaging. Discussions about potential applications for artificial intelligence in radiology have dominated medical imaging conferences and news headlines for years. All the noise and hype can make it hard for imaging providers to know which AI-based
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Diagnostic Imaging Providers Need to be Diligent in Evaluating New Technologies Artificial intelligence (AI) in radiology has been generating significant buzz for several years, and will inevitably play a large and vital role in the future of medical imaging. But what is the cost-benefit analysis
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The technology is not new, but the applications might be surprising. The outlook for diagnostic imaging in 2019 seems very familiar to what Everything Rad reported in 2018. Artificial intelligence (AI) and wearable devices are on the list once again, along with the addition of more apps for mobile
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Easy access to algorithms accelerates development of apps - what will it mean for radiology? By Eliot Siegel, MD, FACR, FSIIM. Want to improve detection of intracranial hemorrhage in a trauma patient? Or quantify the progression of multiple sclerosis? There will be an app for that
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