VLSI Implementation of Medical Image Fusion Using DWT-PCA Algorithms

Abstract

Nowadays, the usage of DIP is more important in the medical field to identify the activities of the patients related to various diseases. Magnetic Resonance Imaging (MRI) and Computer Tomography (CT) scan images are used to perform the fusion process. In brain medical image, MRI scan is used to show the brain structural information without functional data. But, CT scan image is included the functional data with brain activity. To improve the low dose CT scan, hybrid algorithm is introduced in this paper which is implemented in FPGA. The main objective of this work is to optimize performances of the hardware. This work is implemented in FPGA. The combination of Discrete Wavelet Transform (DWT) and Principle Component Analysis (PCA) is known as hybrid algorithm. The Maximum Selection Rule (MSR) is used to select the high frequency component from DWT. These three algorithms have RTL architecture which is implemented by Verilog code. Application Specified Integrated Chips (ASIC) and Field Programmable Gate Array (FPGA) performances analyzed for the different methods. In 180 nm technology, DWT-PCA-IF architecture achieved 5.145 mm 2 area, 298.25 mW power, and 124 ms delay. From the fused medical image, mean, Standard Deviation (SD), entropy, and Mutual Information (MI) performances are evaluated for DWT-PCA method.