A distributed arithmetic hardware architecture for real-time Hough transform based segmentation

Real-time segmentation and tracking of biopsy needles is a very important part of image-guided surgery. Since the needle appears as a straight line in medical images, the Hough transform for straight-line detection is a natural and powerful choice for needle segmentation. However, the transform is computationally expensive, and in the standard form is ineffective for real-time segmentation applications. We propose a dedicated hardware architecture for the Hough transform based on distributed arithmetic (DA) principles that results in a real-time implementation. This architecture exploits the inherent parallelism of the Hough transform, and reduces the overall computation time. This procedure, combined with the parallel structure significantly reduces computation times, thus facilitating real-time implementation. The DA-Hough transform architecture has been implemented using the Xilinx FPGA. For a 256times256 image, the proposed design takes 0.1 ms to 1.2 ms to process the Hough transform when the feature points in the image are varied from 2% to 50% of the total image, which are well within the bounds of real-time operation, and thus can facilitate needle segmentation in real time