Hardware Segmentation on Digital Microscope Images for Acute Lymphoblastic Leukemia Diagnosis Using Xilinx System Generator

Abstract

Image segmentation is considered the most critical step in image processing and helps to analyze, infer and make decisions especially in the medical field. Analyzing digital microscope images for earlier acute lymphoblastic leukemia diagnosis and treatment require sophisticated software and hardware systems. These systems must provide both highly accurate and extremely fast processing of large amounts of image data. In this work, the hardware segmentation framework for Acute Lymphoblastic Leukemia (ALL) images based color histogram of Hue channel of HSV color space is proposed to segment each leukemia image into blasts and background using Field Programmable Gate Array (FPGA). The main purpose of this work is to implement image segmentation framework in a FPGA with minimum hardware resources and low execution time to be suitable enough for medical applications. Hardware framework of segmentation is designed using Xilinx System Generator (XSG) as DSP design tool that enables the use of Simulink models, implemented in VHDL and synthesized for Xilinx SPARTAN-3E Starter kit (XC3S500E-FG320) FPGA.