Technology | Remote Viewing Systems | December 13, 2017

AI Visualize Inc. Debuts Artificial Intelligence Cloud Image Visualization Platform at RSNA 2017

Enterprise solution transmits detailed 2-D or 3-D imaging renderings to users on any internet-enabled device

AI Visualize Inc. Debuts Artificial Intelligence Cloud Image Visualization Platform at RSNA 2017

December 13, 2017 — AI Visualize Inc. debuted its new cloud-based artificial intelligence (AI)-based image analysis and viewing platform at the 2017 Radiological Society of North America (RSNA) Annual Meeting, Nov. 26-Dec. 1 in Chicago. The technology relies on evolution and deep learning algorithms to assess imaging data for diagnostically valuable information not readily apparent through conventional analysis, and transmits detailed 3-D/2-D renderings to users on any internet-enabled device. The technology assists physicians in making the most of today’s data-intensive images for more accurate and precise diagnoses. The advanced interactive platform supports X-ray, ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), 3-D tomosynthesis and digital pathology images, and provides a full range of relevant virtual image analysis tools.

Eliminating the need to communicate large datasets over the internet, the new interactive AI platform processes images in the AI VoXcell cloud using powerful graphics processing unit (GPU) technology. It streams relevant information and imaging tools to users, wherever located, in real time. The same AI technology that processes images also overcomes internet bandwidth and latency limitations by using predictive buffering to provide fast transmission rates over existing communications lines.

Server-side rendering eliminates the need for powerful and costly onsite graphics processors, supporting off-the-shelf supercomputing infrastructure to make the solution scalable and affordable. The AI Visualize technology is covered by 11 international patents. It is U.S. Food and Drug Administration (FDA)-cleared and HIPAA-compliant, supporting high levels of security.

Other capabilities and features of the AI Cloud Visualization Platform include:

Visualization

  • Transmitting a volume visualization dataset (e.g. a 3-D dataset) or a medical imaging dataset, including non-3-D datasets such as for pathology, for secure storage on a remote database via a security device;
  • Utilizing servers to create virtual views of the dataset per requests from a web/internet-based client applications;
  • Accessing the servers with the client application via a security device;
  • Using the client application to display virtual views of the remote dataset generated remotely by the servers;
  • Virtual views are transmitted from the server to the client device as a compressed video stream; and
  • Ensuring the database, storage medium and servers are at a physically secured site.

Cloud bandwidth and latency

  • Display of higher quality parameter frames after completing display of the lower quality parameter frames;
  • Predictive buffering of the virtual views transmitted to client device;
  • Delay of frame requests from the client device to the server in accordance with the latency; and
  • Evolving compression-parameters based on an algorithm that optimizes the compression to  maintain image quality (compression using artificial intelligence)

Cloud visualization artificial intelligence

  • Machine learning algorithms may be applied to the processing of volume visualization datasets;
  • A pattern recognizer determines whether the central application server flags an image view as normal or abnormal and identifies the anomaly in the view;
  • A neural network model determines whether the transfer function-generated image matches the prototype image; and
  • The neural network employs a convolution neural network model.

For more information: www.aivisualize.com

Related Content

Videos | Artificial Intelligence | December 18, 2018
Radiological Society of North America (RSNA) 2018 annual meeting keynote speaker Michael Recht, M.D., chairman of rad
Nicklaus Children's Hospital Launches Enterprise Mobile Clinical Collaboration Platform
News | Enterprise Imaging | December 17, 2018
Enterprise imaging health information technology (IT) provider Dicom Systems Inc. announced a new joint deployment with...
Videos | Enterprise Imaging | December 14, 2018
ITN Editor Dave Fornell and ITN Contributing Editor Greg Freiherr share their insights on the vendors highlighting EI
Videos | Artificial Intelligence | December 13, 2018
ITN Editor Dave Fornell and ITN Contributing Editor Greg Freiherr share their insights on the vendors showing AI prod
Guerbet Showcases Diagnostic and Interventional Imaging Solutions at RSNA 2018
News | Interventional Radiology | December 12, 2018
Guerbet LLC USA highlighted new and next-level product offerings and partnerships in contrast media, injectors,...
Lunit Announces New Prominent Radiology Advisory Board Members
News | Artificial Intelligence | December 11, 2018
Medical artificial intelligence (AI) software company Lunit announced three new members of its advisory board,...
Coreline Soft Introduces AI Lung Segmentation Solution at RSNA 2018
News | Lung Cancer | December 10, 2018
December 10, 2018 — Korean image software company Coreline Soft Co. Ltd.
FDA Clears iCAD's ProFound AI for Digital Breast Tomosynthesis
Technology | Mammography | December 07, 2018
iCAD Inc. announced clearance by the U.S. Food and Drug Administration (FDA) for their latest, deep-learning, cancer...
YITU Releases AI-Based Cancer Screening Solutions at RSNA 2018
News | Artificial Intelligence | December 06, 2018
Chinese artificial intelligence (AI) healthcare company YITU healthcare released two brand-new products, Intelligent...
GE Healthcare Unveils New Applications and Smart Devices Built on Edison Platform
Technology | Artificial Intelligence | December 05, 2018
GE Healthcare recently announced new applications and smart devices built on Edison – a platform that helps accelerate...