News | November 15, 2010

High-Speed Image Gateway Introduced

November 15, 2010 — The new Turbo Gateway is said to deliver images to and from a cloud-based image repository up to 300% faster than existing technologies.

Part of the SeeMyRadiology.com product suite, Turbo Gateway overcomes the limitations of the DICOM transfer protocol to speed data over a conventional internet connection, while continuing to support a standard interface with all picture archiving and communications systems (PACS) and imaging modalities.

The SeeMyRadiology Turbo Gateway is a compact, easy-to-install software, also available as an appliance, that connects directly to a facility’s local area network (LAN). The device maximizes the utilization of available internet bandwidth and optimizes transmission of imaging data in a cloud computing environment. Taking advantage of a new data handling methodology, the device has shown sustained average speeds of 4.5 computed tomography (CT) images/second and 8 magnetic resonance (MR) images/second in benchmark testing over a 10mbps internet connection.

Based on these metrics, distribution times of studies via a cloud environment will be reduced to less than one minute for a 100MB study. Turbo Gateway ensures a high level of security without the need for VPNs and also provides built-in data validation, uptime monitoring and fault tolerance.

Internet image transfer speed is becoming increasingly important as a growing number of imaging providers rely on cloud-based technology to communicate with staff radiologists in multiple locations, offsite teleradiology providers, referring physicians and outside institutions. Radiology practices need fast, streamlined image communications to compete in today’s challenging healthcare environment.

Rapid, easy-to-enable cloud-based image communication can help many sites eliminate the costly and time-consuming production of imaging CDs and provide valuable real-time image communications for trauma transfers and tertiary referrals, resulting in enhanced patient care.

For more information: www.seemyradiology.com or www.accelarad.com

Related Content

Improving Molecular Imaging Using a Deep Learning Approach
News | Nuclear Imaging | March 21, 2019
Generating comprehensive molecular images of organs and tumors in living organisms can be performed at ultra-fast speed...
DrChrono and 3D4Medical Partner to Bring 3-D Interactive Modeling to Physician Practices
News | Advanced Visualization | March 18, 2019
DrChrono Inc. and 3D4Medical have teamed up so practices across the United States can access 3-D interactive modeling...
SyncVision iFR Co-registration from Philips Healthcare maps iFR pressure readings onto angiogram.

SyncVision iFR Co-registration from Philips Healthcare maps iFR pressure readings onto angiogram. Results from an international study presented at #ACC19 show that pressure readings in coronary arteries may identify locations of stenoses remaining after cardiac cath interventions.

Feature | Cardiac Imaging | March 18, 2019 | By Greg Freiherr
As many as one in four patients who undergo cath lab interventions can benefit from a technology that identifies the
Jennifer N. A. Silva, M.D., a pediatric cardiologist at Washington University School of Medicine in Saint Louis, Mo., describes “mixed reality” at ACC19 Future Hub.

Jennifer N. A. Silva, M.D., a pediatric cardiologist at Washington University School of Medicine in Saint Louis, Mo., describes “mixed reality” at ACC19 Future Hub.

Feature | Cardiac Imaging | March 17, 2019 | By Greg Freiherr
Virtual reality (VR) and its less immersive kin, augmented reality (AR), are gaining traction in some medical applica
WVU cardiology chief Partho Sengupta, M.D., describes at ACC 2019 how artificial intelligence already helps cardiologists in echocardiography.

WVU cardiology chief Partho Sengupta, M.D., describes at ACC 2019 how artificial intelligence already helps cardiologists in echocardiography. Photo by Greg Freiherr

Feature | Cardiac Imaging | March 16, 2019 | By Greg Freiherr
Machine learning is already having an enormous impact on cardiology, automatically calculating measurements in echoca
Sponsored Content | Videos | Enterprise Imaging | March 15, 2019
As a VNA, GE Healthcare Ce
Podcast | Cardiac Imaging | March 15, 2019
Debate About Coronary Testing Highlights ACC Session
Podcast | Cardiac Imaging | March 12, 2019
How smart algorithms might reduce the burden of modern practice
Collage provided by Albert Hsiao

Collage depicts broad applications in machine learning or deep learning (DL) that can be applied to advanced medical imaging technologies. Size of the liver and its fat fraction — 22 percent — (top middle in collage) can be quantified automatically using an algorithm developed by Dr. Albert Hsiao and his team at the University of California San Diego. This and other information that might be mined by DL algorithms from CT and MR images could help personalize patients’ treatment. Collage provided by Albert Hsiao

Feature | Cardiac Imaging | March 11, 2019 | By Greg Freiherr
Computed tomography (CT) and magnetic resonance imaging (MRI) scans are chock full of information that might be used
FDA Grants Breakthrough Designation to Paige.AI
News | Digital Pathology | March 08, 2019
Artificial intelligence (AI) startup company Paige.AI has been granted Breakthrough Device designation by the U.S. Food...