Market Overview

Intel and Philips Accelerate Deep Learning Inference on CPUs in Key Medical Imaging Uses

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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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