Picture this: dozens of talks about AI in medical imaging, presented by experts from top radiology departments and academic medical centers around the world, all available free online.
That’s just a slice of GTC Digital, a vast library of live and on-demand webinars, training sessions and office hours from NVIDIA’s GPU Technology Conference.
Healthcare innovators across radiology, genomics, microscopy and more will share the latest AI and GPU-accelerated advancements in their fields through talks on GTC Digital.
Researchers in Sydney, Australia, are using AI to analyze brain scans. In Massachusetts, another is segmenting the prostate gland from ultrasound images to help doctors fine-tune radiation doses. And in Munich, Germany, they’re streamlining radiology reports to foster real-time reporting.
Read more about these standout speakers advancing the use of deep learning in medical imaging worldwide below. And register for GTC Digital for free to see the whole healthcare lineup.
Mental Math: Australian Center Uses AI to Analyze Brain Scans
When studying neurodegenerative disease, quantifying brain tissue loss over time helps physicians and clinical trialists monitor disease progression. Radiologists typically inspect brain scans visually and classify the brain shrinkage as “moderate” or “severe” — a qualitative assessment. With accelerated computing, brain tissue loss can instead be measured precisely and quantitatively, without losing time.
The Sydney Neuroimaging Analysis Centre conducts neuroimaging research as well as commercial image analysis for clinical research trials. SNAC will share at GTC Digital how it uses AI and NVIDIA GPUs to accelerate AI tools that automate laborious analysis tasks in their research workflow.
One model precisely isolates brain images from head scans, segmenting brain lesions for multiple sclerosis cases. The AI reduces the time to segment and determine the volume of brain lesions from up to 15 minutes for a manual examination down to just three seconds, regardless of the number or volume of lesions.
“NVIDIA GPUs and DGX systems are the core of our AI platform, and are transforming the delivery of clinical and research radiology with our AI innovation,” said Tim Wang, director of operations at SNAC. “We are particularly excited by the application of this technology to brain imaging.”
SNAC uses the NVIDIA Clara Train SDK’s AI-assisted annotation tools for model development and the NVIDIA Clara Deploy SDK for integration with clinical and research workflows. It’s also exploring the NVIDIA Clara platform as a tool for federated learning. The center relies on the NVIDIA DGX-1 server, NVIDIA DGX Station and GPU-powered PC workstations for both training and inference of its AI algorithms.
About NVIDIA
NVIDIA (NASDAQ: NVDA) is the AI computing company. Its invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionised parallel computing. More recently, GPU deep learning ignited modern AI – the next era of computing – with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. More information at http://nvidianews.nvidia.com/.