Several new trends have emerged over the past five years in the imaging and informatics field. Using the terminology from the Garter hype cycle  , some of them have not made it beyond the innovation trigger (yet), some ended up at the peak of inflated expectations, others ended up in the trough of disillusionment, and some have emerged to become somewhat mature technologies. I used the hype cycle categorization to show where the top ten trends are right now and where I believe they might end up a year from now.
Radiology artificial intelligence (AI) was again the hottest topic at the 2019 Radiological Society of North America (RSNA) annual meeting in December. AI was a primary theme in the larger booths in the north and south expo floors, as well as on the new third expo floor dedicated AI showcase.
Konica Minolta unveiled a new PACS solution for specialty practices and security enhancement technology last week at the 2019 RSNA annual meeting.
Konica Minolta’s Dynamic Digital Radiography (DDR) is an award-winning enhanced X-ray technology that provides a series of individual digital images acquired at high speed and low dose. The resulting cineloop enables clinicians to observe the motion of anatomical structures over time, improving diagnostic capabilities. Because DDR cines are digital, they can be enhanced, quantified, reprocessed and replayed at normal, fast and, slow motion, as well as one frame at a time (freeze frame).
Konica Minolta Healthcare Advances the Future of Healthcare with New Innovative Imaging and IT Solutions at RSNA 2019
WAYNE, N.J., Nov . 26, 2019 ( GLOBE NEWSWIRE ) — At the 2019 annual meeting of the Radiological Society of North America (RSNA), Konica Minolta Healthcare Americas, Inc. will introduce new innovations in data analytics, digital radiography, enterprise image and data management, ultrasound solutions and alternate care markets at one of the world’s largest medical tradeshows. The company is exhibiting at RSNA 2019 in the South Hall, booth #2538.
Through its structure and scalability, the cloud makes data usable, even when there are volumes of it. A modern form of artificial intelligence (AI), exemplified by deep learning (DL) algorithms, crunches this data so people can make sense of it.
By processing data in the cloud, DL algorithms provide the information that people need to improve workflow and image quality and to optimize patient radiation dose, which directly impacts patient safety. Improvements can elevate the standard of care.
Embedded in the many data sets that comprise it, Big Data may provide an understanding of how health care can be improved. But because its volumes of information can overwhelm traditional means of analysis, valuable patterns may emerge only through the use of deep learning (DL) algorithms. This form of artificial intelligence can transform Big Data into actionable information, giving providers the insights through which they might reduce health care costs and improve care.
The move to DR from CR and conventional analog X-ray systems continues, but the industry is nearing the end of the transition cycle. The image quality and workflow advantages of DR are now benefiting most patients in both mature and emerging markets.
“The most significant new trend in the industry in this context is artificial intelligence applications that promise to improve clinical confidence and efficiency, and there is a lot of AI innovation happening specifically in the X-ray modality,”
Diversity was on display at the Association for Medical Imaging Management (AHRA) 2019 meeting — diversity in the practice of radiology and in product portfolios; diversity that translates into the marketplaces as complexity and uncertainty.
In July, show-goers crammed a symposium titled “Imaging Market Outlook at the AHRA 2019” where Stuart Clark, managing director and national spokesperson, The Advisory Board, described the conflicting and contrary factors that could roil the U.S. marketplace over the coming years.
Researchers from Intermountain Healthcare and Stanford University say 10 seconds is about how quickly a new system they studied that utilizes artificial intelligence (AI) took to accurately identify key findings in chest X-rays of patients in the emergency department suspected of having pneumonia.