Detection of Lung Cancer by Canny Edge Detector for Performance in Area, Latency

Abstract

Lung Cancer is one of the dangerous diseases becoming common in people who are prey to it if it is not identified in time. The present research work explains Random Access Dual-port Memory (DRAM), based on Canny Edge Detection (CED) with efficient Save Carry Adder (CSA) and Look-ahead Carry Adder (CLA) and Skip Carry Adder (CSkipA) are introduced. Improving the edge detection performance by employing DRAM and an efficient optimal adder, which is called as DRAM-Optimal Adders-CED system is the main objectives of this research work. The lung cell images are read by MATLAB. The DRAM-Optimal Adder-CED system is implemented in Xilinx tool based on Virtex-6 device with different families such as xc6vcx75t, xc6vcx130t and xc6vcx195t with code in verilog. The DRAM-Optimal Adder-CED method mainly improves the Field Programmable Gate Array (FPGA) performance parameters such as Look-up-Table, slice, flip-flop, frequency and power. The DRAM-Optimal Adder-CED methodology improves the average FPGA performances about 22.76% of LUT, 8.47% of flip-flop and 28.14% of slice with that of existing techniques such as CED-FPGA and DBRAM-CSLA-CED method.