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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vRad announces new patent for escalating radiology procedures through AI

vRad, a MEDNAX company, announced this week that it has secured a patent for using artificial intelligence (AI) to escalate high-priority radiology procedures.

Researchers use machine learning to detect fractures in plain radiographs

Machine learning using deep convolutional neural networks (CNNs) can be used to detect fractures in plain radiographs, according to a new study published in Clinical Radiology.

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Software using machine learning algorithms accurately audits radiologist compliance

Imaging groups throughout the United States have moved to standardized radiology reports in recent years, and it’s a trend that continues to pick up steam. One side effect of this change is that leaders must then perform long, labor-intensive manual audits of their team’s reports to confirm compliance. But what if groups could somehow perform an automated audit, making those pesky manual audits a thing of the past?

GE and NVIDIA Join Forces to Accelerate Artificial Intelligence Adoption in Healthcare

GE Healthcare and NVIDIA today announced they will deepen their 10-year partnership to bring the most sophisticated artificial intelligence (AI) to GE Healthcare’s 500,000 imaging devices globally and accelerate the speed at which healthcare data can be processed.

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Just the beginning: 6 applications for machine learning in radiology beyond image interpretation

Discussions about machine learning’s impact on radiology might begin with image interpretation, but that’s only the tip of the iceberg. When it comes to realizing the technology’s full potential, it’s like Bachman Turner Overdrive sang many years ago: You ain’t seen nothing yet.

ICAD RECEIVES FDA APPROVAL FOR POWERLOOK TOMO DETECTION

First to market with innovative digital breast 3D tomosynthesis cancer detection and workflow solution, built on deep learning technology that improves efficiency and reduces reading time for radiologists

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First Patient Treated With LC Bead LUMI™ Radiopaque Embolic Bead Supported by Philips Live Image Guidance

Collaboration brings new tools to interventional radiologists and oncologists to help treat liver cancer and enhanced patient care.

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Around the web

Health Imaging
Nearly $800,000 settlement offered to family of man who died during MRI exam

The patient, who was being cared for in the ICU, was not accompanied or monitored by nursing staff during his exam, despite being sedated.

Cardiovascular Business
Global shortage of nuclear imaging isotopes may be over

The nuclear imaging isotope shortage of molybdenum-99 may be over now that the sidelined reactor is restarting. ASNC's president says PET and new SPECT technologies helped cardiac imaging labs better weather the storm.

Cardiovascular Business
‘A huge win’: CMS significantly increases Medicare payments for cardiac CT

CMS has more than doubled the CCTA payment rate from $175 to $357.13. The move, expected to have a significant impact on the utilization of cardiac CT, received immediate praise from imaging specialists.