News | Artificial Intelligence | February 22, 2017

TeraRecon Demonstrates Deep Learning Workflow at HIMSS17

Prototype WIA Cloud engines learn from physician-driven workflow and improve automation in real-time

TeraRecon, deep learning workflow, HIMSS17, WIA Cloud, machine learning, artificial intelligence

February 22, 2017 — TeraRecon is demonstrating their Within Image Analysis (WIA) Cloud machine learning solution this week at the Healthcare Information & Management Systems Society (HIMSS17) Conference and Exhibition, Feb. 19-24 in Orlando, Fla. WIA Cloud aims to accelerate and automate image interpretation and advanced post-processing tasks using artificial intelligence to eliminate repetitive operator tasks.

WIA Cloud is a platform that can provide access to closed-loop, semi-automated ground-truth machine learning engines and artificial intelligence algorithms. This platform will have the ability to rapidly impact clinical applications and deliver customized workflow enhancements by providing a wide range of artificial intelligence and machine learning engines that identify, categorize and characterize images. The platform will integrate to third-party applications and learn end-user behaviors, all the while allowing physicians to independently validate the macro-level indications of each engine’s output.

In addition, the company announced the full general-availability release of its turbo-performance Volume Pro (VP) CUDA interface layer, readying the platform for nVidia CUDA GPUs and eliminating the need for previously required proprietary hardware. All current and future customers will have the opportunity to affordably upgrade to this new technology, which provides a 400 percent increase in system performance.

Currently, TeraRecon’s iNtuition advanced visualization platform is on display running both VP CUDA and a prototype WIA Cloud engine that suggests image classifications on cardiac magnetic resonance (MR) studies, as well as other engines and features, at HIMSS.

WIA Cloud is currently in development as an application of iNtuition Cloud.

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