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. This paper proposes a dedicated hardware architecture for the Hough transform based on distributed arithmetic (DA) principles that results in a real-time implementation. The architecture exploits the inherent parallelism of the Hough transform and reduces the overall computation time. The DA Hough transform architecture has been implemented using the Xilinx field-programmable gate array (FPGA). For a 256x256-bit image, the proposed design takes between 0.1 ms and 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; these values are well within the bounds of real-time operation and thus can facilitate needle segmentation in real time.