Intel and Philips Accelerate Deep Learning Inference on CPUs in Key Medical Imaging Uses
August 14 2018 - 4:00PM
Business Wire
What’s New: Using Intel® Xeon® Scalable processors and
the OpenVINO™ toolkit, Intel and Philips* tested two healthcare use
cases for deep learning inference models: one on X-rays of bones
for bone-age-prediction modeling, the other on CT scans of lungs
for lung segmentation. In these tests, Intel and Philips achieved a
speed improvement of 188 times for the bone-age-prediction model,
and a 38 times speed improvement for the lung-segmentation model
over the baseline measurements.
“Intel Xeon Scalable processors appear to be
the right solution for this type of AI workload. Our customers can
use their existing hardware to its maximum potential, while still
aiming to achieve quality output resolution at exceptional
speeds.”
-- Vijayananda J., chief architect and
fellow, Data Science and AI at Philips HealthSuite Insights
Why It’s Important: Until recently, there was one
prominent hardware solution to accelerate deep learning: graphics
processing unit (GPUs). By design, GPUs work well with images, but
they also have inherent memory constraints that data scientists
have had to work around when building some models.
Central processing units (CPUs) – in this case Intel Xeon
Scalable processors – don’t have those same memory constraints and
can accelerate complex, hybrid workloads, including larger,
memory-intensive models typically found in medical imaging. For a
large subset of artificial intelligence (AI) workloads, Intel Xeon
Scalable processors can better meet data scientists’ needs than
GPU-based systems. As Philips found in the two recent tests, this
enables the company to offer AI solutions at lower cost to its
customers.
Why It Matters: AI techniques such as object detection
and segmentation can help radiologists identify issues faster and
more accurately, which can translate to better prioritization of
cases, better outcomes for more patients and reduced costs for
hospitals.
Deep learning inference applications typically process workloads
in small batches or in a streaming manner, which means they do not
exhibit large batch sizes. CPUs are a great fit for low batch or
streaming applications. In particular, Intel Xeon Scalable
processors offer an affordable, flexible platform for AI models –
particularly in conjunction with tools like the OpenVINO toolkit,
which can help deploy pre-trained models for efficiency, without
sacrificing accuracy.
These tests show that healthcare organizations can implement AI
workloads without expensive hardware investments.
What the Results Show: The results for both use cases
surpassed expectations. The bone-age-prediction model went from an
initial baseline test result of 1.42 images per second to a final
tested rate of 267.1 images per second after optimizations – an
increase of 188 times. The lung-segmentation model far surpassed
the target of 15 images per second by improving from a baseline of
1.9 images per second to 71.7 images per second after
optimizations.
What’s Next: Running healthcare deep learning workloads
on CPU-based devices offers direct benefits to companies like
Philips, because it allows them to offer AI-based services that
don’t drive up costs for their end customers. As shown in this
test, companies like Philips can offer AI algorithms for download
through an online store as a way to increase revenue and
differentiate themselves from growing competition.
More Context: Multiple trends are contributing to this
shift:
- As medical image resolution improves,
medical image file sizes are growing – many images are 1GB or
greater.
- More healthcare organizations are using
deep learning inference to more quickly and accurately review
patient images.
- Organizations are looking for ways to
do this without buying expensive new infrastructure.
The Philips tests are just one example of these trends in
action. Novartis* is another. And many other Intel customers – not
yet publicly announced – are achieving similar results. Learn more
about Intel AI technology in healthcare at "Advancing Data-Driven
Healthcare Solutions."
About Intel
Intel (NASDAQ: INTC) expands the boundaries of technology to
make the most amazing experiences possible. Information about Intel
can be found at newsroom.intel.com and intel.com.
Intel and the Intel logo are trademarks of Intel Corporation in
the United States and other countries.
*Other names and brands may be claimed as the property of
others.
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IntelRobin Holt, 503-696-2735robin.holt@intel.com
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