The Performance Enhancement of Image Segmentation Technique based on VLSI Technology

Image segmentation is essential when processing images for medical purposes. The weak image contrast and scattered organ or tissue borders make it challenging to segment medical images. Due to significant developments in engineering technology, many diagnostic procedures in medicine are now automated and use image processing techniques. VLSI design’s purpose in medical image segmentation is to offer quick and effective hardware solutions for identifying anatomical structure boundaries in a variety of medical pictures. Very large-scale integration, or VLSI, is a technique for building integrated circuits by fusing millions of transistors onto a single chip. The performance, speed, accuracy, and power consumption of image segmentation algorithms, which are frequently computationally demanding and complicated, can be improved through VLSI design. Thus, in this study, the Xilinx System Generator (XSG) and FPGA are used to implement the segmentation of brain tumors on hardware. Due to extensive parallelism and pipelining, it beats conventional programmable digital signal processorsand even Personal Computer with coprocessors in terms of performance, design time, and cost. The complexity of architectural design is significantly reduced when using XSG for medical image processing applications. Additionally, the potential of hardware co-simulation is offered.