News | Artificial Intelligence | April 27, 2018

Medical imaging vendor teaming with graphics processing unit developer NVIDIA to launch AI solution to mine healthcare data

NVIDIA, Canon Medical Systems Partner to Accelerate Deep Learning in Healthcare

April 27, 2018 — Computer technology company NVIDIA and Canon Medical Systems announced a new partnership to develop the research infrastructure for enhanced artificial intelligence (AI) in healthcare. The partners hope to make a significant contribution to promoting the use of data-intensive deep learning techniques in medical and related research, as well as to drive the uptake of AI in the healthcare sector.

According to NVIDIA, the healthcare sector needs to analyze scientific reports from around the world, while simultaneously coordinating a variety of patient data to determine the most appropriate treatment options. Given the huge volumes of data involved, big data analysis via deep learning will play a major role in the development of optimized healthcare delivery systems and support early detection and assisted diagnosis.

At the same time, medical institutions wanting to use deep learning for independent research need hardware for analysis, systems for the collection, collation and analysis of in-house data, and knowledge of deep learning processes and techniques.

Canon Medical Systems will use NVIDIA DGX systems to process large volumes of medical data generated by Abierto VNA (vendor neutral archive), the proprietary, in-house medical data management system it launched in January.

DGX systems feature NVIDIA Tesla data center graphics processing units (GPUs) powered by the Volta advanced GPU architecture. Among the portfolio is NVIDIA DGX Station, an AI workstation that has the computing capacity of four server racks in a desk-friendly package, while consuming only 1/20 the power.

The systems include NVIDIA’s specially optimized AI software and Canon Medical System’s graphical user interface, which provides full support for the design, deployment and operation of advanced deep learning algorithms.

Deep learning usually requires extensive programming and data science skills. However, the system from Canon Medical Systems and NVIDIA guides users through all the steps involved in the deep learning process, from generating training data with the image viewer to setting up the NVIDIA learning environment.

For more information: www.us.medical.canon

 


Related Content

News | Breast Imaging

Aug. 28, 2024 — Rezolut, LLC recently debuted its latest offering for patients during their annual mammogram ...

Time August 29, 2024
arrow
News | Digital Pathology

Paige has launched OmniScreen, an AI-driven biomarker module capable of evaluating over 505 genes and detecting 1,228 ...

Time August 27, 2024
arrow
News | RSNA

July 31, 2024 — The National Imaging Informatics Course (NIIC), a pioneering program in the radiology field, will return ...

Time July 31, 2024
arrow
Feature | Radiation Oncology | By Christine Book

News emerging from several leading organizations and vendors in the radiation therapy arena came in at a fast pace in ...

Time July 30, 2024
arrow
News | Breast Imaging

July 29, 2024 — Lunit, a leading provider of AI-powered solutions for cancer diagnostics and therapeutics, announced the ...

Time July 29, 2024
arrow
News | Breast Imaging

July 29, 2024 — iCAD, Inc., a global leader in clinically proven AI-powered cancer detection solutions, announced a ...

Time July 29, 2024
arrow
News | Artificial Intelligence

July 26, 2024 — GE HealthCare and Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company, announced a strategic ...

Time July 26, 2024
arrow
Videos | Information Technology

Industry trade shows and conferences seem to be making their comeback in 2024. And the Healthcare Information and ...

Time July 25, 2024
arrow
News | Digital Pathology

July 24, 2024 — Proscia, a developer of artificial intelligence (AI)-enabled digital pathology solutions for precision ...

Time July 24, 2024
arrow
Videos | Breast Imaging

Don't miss ITN's latest "One on One" video interview with AAWR Past President and American College of Radiology (ACR) ...

Time July 24, 2024
arrow
Subscribe Now