Employing Parallel Hardware Architectures to Diagnose Sickle Cell Anemia in Real-Time Basis

Among the solid components of the human blood, the type that has the largest number of them is well known as red blood cells (RBCs). These cells have flat-round shapes, where their centers are depressed like a doughnut missing its hole. When the cell shape is changed from circular to sickle, then this case is a blood disease named sickle cell anemia (SCA). Based on its number, the dangerous level is obtained. This paper employs parallel hardware architectures to detect the sickle cells and its dangerous level in a real-time basis. These parallel architectures include the field programmable gated array (FPGA) and the graphical processing unit (GPU). In addition, the central processing unit (CPU) as the common serial architecture is also employed for comparison basis in terms of time consuming and power consumption. The circular Hough Transform (CHT) method is employed for detecting the sickle cells. To determine the dangerous level, the number of sickle cells and the number of normal ones are counted. The detection, counting, and classification algorithms are all coded in the Verilog language (for the FPGA) and in the MATLAB software (for the GPU and CPU). The findings have achieved well-behaved performances and acceptable results are obtained.