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.

Related Content

Machine Learning IDs Markers to Help Predict Alzheimer's

Neurologists use structural and diffusion magnetic resonance imaging (MRI) to identify changes in brain tissue (both gray and white matter) that are characteristic of Alzheimer's disease and other forms of dementia. The MRI images are analyzed using morphometry and tractography techniques, which detect changes in the shape and dimensions of the brain and in the tissue microstructure, respectively. In this example, the images show the normal brain of an elderly patient. Image courtesy of Jiook Cha.

News | Neuro Imaging | September 20, 2018
New research has shown a combination of two different modes of magnetic resonance imaging (MRI), computer-based...
LVivo EF Cardiac Tool Now Available for GE Vscan Extend Handheld Mobile Ultrasound
Technology | Cardiovascular Ultrasound | September 19, 2018
DiA Imaging Analysis Ltd. (DiA), a provider of artificial intelligence (AI)-powered ultrasound analysis tools,...
Exact Imaging Partners to Improve Prostate Cancer Detection With Artificial Intelligence
News | Prostate Cancer | September 19, 2018
Exact Imaging, makers of the ExactVu micro-ultrasound platform, has partnered with U.K.-based Cambridge Consultants to...
SimonMed Deploys ClearRead CT Enterprise Wide
News | Computer-Aided Detection Software | September 17, 2018
September 17, 2018 — National outpatient physician radiology group SimonMed Imaging has selected Riverain Technologie
Acuson Sequoia
News | Ultrasound Imaging | September 12, 2018
Siemens Healthineers announced the first global installation of its newest ultrasound system, the...
Veye Chest version 2
News | Lung Cancer | September 11, 2018
Aidence, an Amsterdam-based medical AI company, announced that Veye Chest version 2, a class IIa medical device, has
Sponsored Content | Case Study | Information Technology | September 07, 2018
Established in 1970, Sovah Health – Martinsville, Va., resides in the foothills of the beautiful Blue Ridge Mountains...
Feature | Population Health | September 07, 2018 | By Jeff Zagoudis
Over the last several years in the U.S., healthcare providers have been trying to shift their focus to more preventive...
Sponsored Content | Case Study | Information Technology | September 07, 2018
One of the Northeast’s major teaching hospitals is an international leader in virtually every area of medicine. It has...
The CT scanner might not come with protocols that are adequate for each hospital situation, so at Phoenix Children’s Hospital they designed their own protocols, said Dianna Bardo, M.D., director of body MR and co-director of the 3D Innovation Lab at Phoenix Children’s.

The CT scanner might not come with protocols that are adequate for each hospital situation, so at Phoenix Children’s Hospital they designed their own protocols, said Dianna Bardo, M.D., director of body MR and co-director of the 3D Innovation Lab at Phoenix Children’s.

Sponsored Content | Case Study | Radiation Dose Management | September 07, 2018
Radiation dose management is central to child patient safety. Medical imaging plays an increasing role in the accurate...