Health and Life Sciences at the Edge: Advancements in Medical Imaging Processing

In this episode of Health and Life Sciences at the Edge, host Tyler Kern speaks with Beenish Zia, an electrical engineer working as a platform architect in Health and Life Sciences at Intel, and Joy Yun, who interned in Health and Life Sciences at Intel, about the technological advances fueling the rapid expansion of the medical imaging industry.

The U.S. Food and Drug Administration defines medical imaging as several different technologies used to view the human body to diagnose, monitor, or treat medical conditions. Each type of technology gives different types of information about the area of the body being studied or treated. Examples include Ultrasound, X-ray, magnetic resonance imaging (MRI), and computer tomography (CT).

According to a market insights report by Research and Markets, the global medical imaging market size is expected to reach $28.6 billion by 2028. Zia attributes this rapid growth to advances in medical imaging hardware and software. “These advances include a variety of technical improvements,” says Zia, “from the devices that generate the raw data to how data is processed, stored, and transferred before it can be viewed by a radiologist or a healthcare technician.”

Three specific developments are driving advances in medical image processing:

• Convolutions and Cross-correlations: Software processes used to identify issues and refine, adjust, or modify image quality.
• Parallel Programming: Allows the effective distribution of workloads over the computational resources available.
• oneAPI Implementation: oneAPI is a cross industry, open standards-based, unified programming model that allows developers to write code in a common language, thereby enabling companies to code without having to learn three or more language constructs. “I believe oneAPI will provide developers with faster application performance, more productivity, and hopefully greater innovation effect,” says Yun.

According to Zia, another major advantage to using oneAPI, including Intel’s oneAPI implementation, is that it has the potential to end hardware-vendor lock-in. “Historically, when developers needed to move their application to a new hardware or target device based on a different architecture than what they were using, they would have to create an entirely new code base,” says Zia. “Those extra costs and delays are never welcome.” The goal of Intel’s oneAPI implementation is threefold:

• Increase application portability
• Raise developer productivity
• Deliver peak performance to high-growth applications in data centers, at the Edge, and in the Cloud.

To learn more:

• Connect with Beenish Zia on LinkedIn.
• Take a look at these two white papers: Fast Fourier Transform (FFT) and Convolution in Medical Image Reconstruction: https://www.intel.com/content/www/us/en/developer/articles/technical/fast-fourier-transform-and-convolution-in-medical-image-reconstruction.html oneAPI for Healthcare: C++ to DPC++ Migration Example: https://www.intel.com/content/www/us/en/developer/articles/technical/oneapi-cpp-to-dpcpp-conversion.html?wapkw=beenish%20zia
• Listen to our oneAPI in DevFest presentation with GE Healthcare:

If you are a developer interested in using oneAPI, visit “oneAPI: A New Era of Heterogeneous Computing: https://www.intel.com/content/www/us/en/developer/tools/oneapi/overview.html#gs.fgsjop