In this design-in, AMD's Embedded Radeon HD 7850 GPU is used to enhance performance for the BK Ultrasound, powered by Analogic, bk3000 ultrasound system.
Analogic, based close to Boston, Massachusetts, develops imaging and real-time guidance technologies for disease diagnosis and treatment as well as for automated threat detection. Its ultrasound systems, led by the flagship BK Ultrasound brand, is used in procedure-driven markets such as urology, surgery, and point-of-care,by clinical practitioners around the world. Its imaging technologies are also used in computed tomography (CT), magnetic resonance imaging (MRI) and digital mammography systems, as well as automated threat detection systems for aviation security. The company says its imaging technology can be found in over half of the CT and MRI systems installed worldwide.
Analogic used the OpenCL standard to gain access to the AMD graphics processing unit (GPU) for general-purpose (GP) computing, referred to as “GPGPU,” delivering performance and offering system and development cost reduction through cross-platform portability. As a result of using AMD GPU technology, Analogic achieved a 3x improvement in the amount of information in each ultrasound image and reduced time from capture to presentation. Traditional FPGAs and DSPs, AMD asserts, create a fixed, inflexible implementation that requires custom software targeted at specific hardware. Going to a software-based solution using OpenCL helps to further lower the development cost and provides improved long term value since the software can be used across product lines and through generation shifts.
“It was a critical design goal for us to implement a platform that delivered exceptional performance,” said Jacques Coumans, chief marketing and scientific officer, Analogic. “After reviewing the options available, we chose the AMD Embedded Radeon HD 7850 GPU for its excellent quality and scalability. The bk3000 ultrasound system, powered by AMD embedded graphics technology, delivers exceptional speed and image fidelity, which allows clinicians to identify anatomy and flow dynamics deeper in challenging patients.”
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