Medical Development Platform Using ZyCAP-Based Partial Reconfiguration on ZynqSoC

Abstract

Analysis of medical image is important in many biomedical applications such as abnormality detection, diagnosis, and surgical planning. Especially, edge detection of medical images is essential for segmentation and automatic recognition of the human organs. However, performance of edge detection filter degrades significantly if medical images/videos are corrupted with noises. In this paper, Zynq SoC is used as a medical development platform to implement real-time edge detection of image/video sequences of up to 1080p-resolution. Dynamic partial reconfigurable capability is utilized so that adaptive reconfiguration of partial filter bitstreams is performed according to the detected noise density level in the image/video sequences. Moreover, open source controller, called ZyCAP, is implemented on the proposed platform to further increase the reconfiguration speed through DMA controller, which is connected to high performance port for efficient access to external DRAM memory. We demonstrate that the proposed reconfigurable platform increases the accuracy of edge detection results by adaptive partial reconfiguration and adopted ZyCAP controller enables about 2.2 times faster reconfiguration when compared to Processor Configuration Access Port (PCAP).