Greg Freiherr, Industry Consultant
Greg Freiherr, Industry Consultant

Greg Freiherr has reported on developments in radiology since 1983. He runs the consulting service, The Freiherr Group.

Sponsored Content | Blog | Greg Freiherr, Industry Consultant | Artificial Intelligence | January 12, 2020

BLOG: Artificial Intelligence May Help Enterprise Imaging

The latest version of the universal viewer shown by GE Healthcare at RSNA 2019 incorporates artificial intelligence

The latest version of the universal viewer shown by GE Healthcare at RSNA 2019 incorporates artificial intelligence. Image courtesy of GE Healthcare

After languishing for years, enterprise imaging appears ready to enter the mainstream of health care. At least a small part of that may involve the use of artificial intelligence (AI) to make the transmission, storage, display and analysis of the many different types of images easier and more efficient.

At RSNA 2019, GE Healthcare addressed the crossover of AI and enterprise imaging with the latest version of its AI-enabled Centricity Universal Viewer.

Version 7 “consumes” and displays AI findings revealed by the Centricity PACS, said Veena Haravu, Senior Product Manager for Centricity PACS at GE Healthcare. This Version 7, which is pending FDA clearance, is integrated with the company’s Edison Open AI Orchestrator to display the results of smart algorithms embedded in it.

Centricity PACS customers planning to take advantage of the AI being built into Orchestrator (which runs on Centricity PACS) should go with Version 7, Haravu told ITN from the GE Healthcare booth at RSNA 2019.

“The GE (Healthcare Centricity Universal) Viewer is an enterprise viewer in use today with many of our customers worldwide,” she said. “So (V7) is not a new application — or a new widget or a new pop-up for you to work with. (Rather) it is woven into (Centricity Universal Viewer’s) existing reading and reporting workflow so you don’t have to spend a lot of time clicking and accessing other applications.”

 

Making The Future More Efficient

Compatibility with AI algorithms being built into the Orchestrator may be a compelling reason to purchase the latest version of this Viewer. But it is not the only one. Even more compelling may be customers’ need to operate more efficiently in enterprise imaging.

“If you want a cross-enterprise capability that is much enhanced from what it is now — like automatic hanging access of remote comparisons and advanced image placement utilities to make your reading/reporting workflow much more efficient – then V7,” Haravu said. “Version 7 takes what V6 has and enhances it further, giving you (access to) an AI platform.”

Universal viewers have long played an indispensable role in enterprise imaging. These viewers display radiological and optical images as well as charts, graphs and text. Similar to them in operation, the GE Healthcare Universal Viewer is web-based and creates no footprint; its computing is done on Centricity PACS.

Version 7 adds artificial intelligence to the mix by enabling the Universal Viewer to work with the company’s Edison Open AI Orchestrator. Version 7 will work with all the AI algorithms embedded in the Orchestrator, Haravu said. Customers can “have a more seamless workflow,” she said.

 

Reducing Strain on Radiologists

AI and, by extension, the AI-enabled version of GE Healthcare’s Universal Viewer promise to relieve some of the strain responsible for radiologist burnout.

“Burnout is getting a lot of attention,” said Stuart Pomerantz, M.D., a neuroradiologist and researcher at the Center for Clinical Data Science at Massachusetts General Hospital and Brigham and Women’s Hospital.

Burnout is a concern for radiology professionals, according to the American College of Radiology.

Version 7 of the Universal Viewer enables the future, while emphasizing ease of use.

 

Editor’s note: This is the final blog in a series of four blogs about how artificial intelligence might increase both efficiency and effectiveness, thereby, decreasing stress. The first blog, How Burnout Puts Radiology at Risk, can be found here. The second blog, How AI Could Make Radiologists’ Jobs Less Stressful, can be found here. The third blog, BLOG: How AI Might Boost Efficiency and Effectiveness, can be found here.

 

Related content:

BLOG: How AI Might Boost Efficiency and Effectiveness

BLOG: How AI Could Make Radiologists’ Jobs Less Stressful

BLOG: How Burnout Puts Radiology at Risk

Centricity Universal Viewer: Embrace the Power of One Intelligent Diagnostic Viewer

Related Content

Table 1. Compared to 2-D mammography, which yields four images per patient, digital breast tomosynthesis (DBT), or 3-D mammography, produces hundreds of images per patient. While this provides more information for clinicians, the exponential increase in data can result in reader fatigue and burnout, which may ultimately affect patient care.

Table 1. Compared to 2-D mammography, which yields four images per patient, digital breast tomosynthesis (DBT), or 3-D mammography, produces hundreds of images per patient. While this provides more information for clinicians, the exponential increase in data can result in reader fatigue and burnout, which may ultimately affect patient care.

Sponsored Content | Case Study | Artificial Intelligence | April 09, 2020
As the largest independent imaging group in Michigan with 10 locations across the state,...
The interior of the German air force Airbus A-310 Medivac in Cologne, Germany, before its departure to Bergamo, Italy, March 28 to being ferrying COVID-19 patients to Germany for treatment to aid the Italians, whose healthcare system has been overwhelmed by the rapid spread of the coronavirus pandemic. Bundeswehr Photo by Kevin Schrief.

The interior of the German air force Airbus A-310 Medivac in Cologne, Germany, before its departure to Bergamo, Italy, March 28 to being ferrying COVID-19 patients to Germany for treatment to aid the Italians, whose healthcare system has been overwhelmed by the rapid spread of the coronavirus pandemic. Bundeswehr Photo by Kevin Schrief. Find more images from the COVID-19 pandemic.

 

Feature | Coronavirus (COVID-19) | April 08, 2020 | By Melinda Taschetta-Millane and Dave Fornell
In an effort to keep the imaging field updated on the latest information being released on coronavirus (COVID-19), th
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2  The first of three clinical scenarios presented to the panel with final recommendations. Mild features refer to absence of significant pulmonary dysfunction or damage. Pre-test probability is based upon background prevalence of disease and may be further modified by individual’s exposure risk. The absence of resource constraints corresponds to sufficient availability of personnel, personal protective equipment, COVID-19 testing, hospital beds, and/or ve

 The first of three clinical scenarios presented to the panel with final recommendations. Mild features refer to absence of significant pulmonary dysfunction or damage. Pre-test probability is based upon background prevalence of disease and may be further modified by individual’s exposure risk. The absence of resource constraints corresponds to sufficient availability of personnel, personal protective equipment, COVID-19 testing, hospital beds, and/or ventilators with the need to rapidly triage patients. Contextual detail and considerations for imaging with CXR (chest radiography) versus CT (computed tomography) are presented in the text. (Pos=positive, Neg=negative, Mod=moderate). [Although not covered by this scenario and not shown in the figure, in the presence of significant resources constraints, there is no role for imaging of patients with mild features of COVID-19.] Image courtesy of the journal Radiology

News | Coronavirus (COVID-19) | April 07, 2020
April 7, 2020 — A multinational consens...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2 Chest CT findings of pediatric patients with COVID-19 on transaxial images. (a) Male, 2 months old, 2 days after symptom onset. Patchy ground-glass opacities GGO in the right lower lobe

Chest CT findings of pediatric patients with COVID-19 on transaxial images. Male, 2 months old, 2 days after symptom onset. Patchy ground-glass opacities GGO in the right lower lobe. Image courtesy of Radiology: Cardiothoracic Imaging

News | Coronavirus (COVID-19) | April 06, 2020
April 6, 2020 — Children and teenagers with COVID-19...
A recent study earlier this year in the journal Nature, which included researchers from Google Health London, demonstrated that artificial intelligence (AI) technology outperformed radiologists in diagnosing breast cancer on mammograms
Feature | Breast Imaging | April 06, 2020 | By Samir Parikh
A recent study earlier this year in the journal Nature,
Varian received FDA clearance for its Ethos therapy in February 2020. It is an adaptive intelligence solution that uses onboard AI in the treatment system to take the cone beam CT imaging on the system, compare it to the treatment plan and deliver an entire adaptive treatment plan in a typical 15-minute treatment time slot, from patient setup through treatment delivery.

Varian received FDA clearance for its Ethos therapy in February 2020, shown here displayed for the first time at ASTRO 2019. It is an adaptive intelligence solution that uses onboard AI in the treatment system to take the cone beam CT imaging on the system, compare it to the treatment plan and deliver an entire adaptive treatment plan in a typical 15-minute treatment time slot, from patient setup through treatment delivery.

Feature | Treatment Planning | April 03, 2020 | Dave Fornell, Editor
The traditional treatment planning process takes days to create an optimized radiation therapy delivery plan, but new
An example of Philips’ TrueVue technology, which offers photo-realistic rendering and the ability to change the location of the lighting source on 3-D ultrasound images. In this example of two Amplazer transcatheter septal occluder devices in the heart, the operator demonstrating the product was able to push the lighting source behind the devices into the other chamber of the heart. This illuminated a hole that was still present that the occluders did not seal.

An example of Philips’ TrueVue technology, which offers photo-realistic rendering and the ability to change the location of the lighting source on 3-D ultrasound images. In this example of two Amplazer transcatheter septal occluder devices in the heart, the operator demonstrating the product was able to push the lighting source behind the devices into the other chamber of the heart. This illuminated a hole that was still present that the occluders did not seal. Photo by Dave Fornell

Feature | Radiology Imaging | April 02, 2020 | By Katie Caron
A new year — and decade — offers the opportunity to reflect on the advancements and challenges of years gone by and p
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus

Getty Images

Feature | Coronavirus (COVID-19) | April 02, 2020 | Jilan Liu and HIMSS Greater China Team
Information technologies have played a pivotal role in China’s response to the novel coronavirus...