The team had to integrate extremely sensitive sensors with high-speed digital processing capabilities onto a highly integrated low-profile enclosure, and ensure scalability by easily adapting to different sensor sizes.
The architecture was designed to benefit from FPGA fabric performances and multiple ARM cores flexibility, some of which can be used with operating systems that need to be certified for critical applications required in the healthcare industry.
After capturing high-speed raw data from the sensor, the custom video DMA reorganizes the full image in external memory. When all the pixels of the image are correctly reordered, the FPGA can enhance image quality.
The hardware design had to minimize noise, integrate high-speed digital with ultra-low noise circuits, and accommodate physical dimensions constraints and safety considerations. For optimal speed and power consumption, DDR4 memory is used to store local frame buffers, and support acquisition at a fast frame rate.
Analogic’s detector software running in the Zynq UltraScale+ hardware platform is divided into different applications. These applications manage non-critical background tasks with Linux and real-time control of the image datapath on the FPGA side.
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