Melinda Taschetta-Millane, Editorial Director
Melinda Taschetta-Millane, Editorial Director
Blog | Melinda Taschetta-Millane, Editorial Director | Artificial Intelligence| March 02, 2017

Deep Learning in Medical Imaging

artificial intelligence

Photo courtesy of Philips Healthcare

Artificial intelligence (AI), or deep learning, continues to be an ongoing topic of conversation. According to a new report by Signify Research, an independent supplier of market intelligence and consultancy to the global healthcare information technology industry, this will lead to a $300 million market by 2021. 

The report stresses that in most countries, there are not enough radiologists to meet the ever-increasing demand for medical imaging, and many radiologists are already working at full capacity. It’s likely the situation will worsen as imaging volumes increase faster than new radiologists can enter the field. 

A new breed of image analysis software has emerged that uses deep learning to help alleviate some of the more repetitive and time-consuming tasks routinely performed by radiologists. This growing array of products automates the various stages of the imaging diagnosis workflow.

“Radiology is evolving from a largely descriptive field to a more quantitative discipline. Intelligent software tools that combine quantitative imaging and clinical workflow features will not only enhance radiologist productivity, but also improve diagnostic accuracy,” said Simon Harris, principal analyst at Signify Research and author of the report.

But it is still early in the game for deep learning in medical imaging. Few products are available, and it remains unclear how deep learning will deal with multiple variations in protocols and procedures. And, many radiologists remain skeptical.

“Deep learning is a truly transformative technology and the longer-term impact on the radiology market should not be underestimated. It’s more a question of when, not if, machine learning will be routinely used in imaging diagnosis,” Harris concluded.

If you want to learn more about the Signify Research study, visit http://bit.ly/2lnCEau.

 

ITN a Neal Awards Finalist

Also, I’m proud to announce that ITN is again a finalist in the prestigious Neal Awards editorial excellence competition in the category “Best Commentary/Blog” for Greg Freiherr’s ongoing Last Read column. (You can read Greg’s latest column on page 34 of this issue.) Now in its 63rd year, the Neal Awards recognize the best in business-to-business editorial across standalone and integrated media channels. Dubbed “the Pulitzer Prize of business media,” the Neal Awards are b-to-b’s most prestigious and sought-after editorial honors. 

ITN’s sister publication, Diagnostic and Interventional Cardiology (DAIC), is also a finalist in the category of “Best Use of Social Media.” Winners of all categories will be announced in early April.

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