Digital image processing is nowadays widely used in biomedical applications. Counting of the red blood cells from the blood smear images can help in detecting anemia. Since the manual location, identification and counting of red blood cells is a tedious, error prone and time consuming there is a rising need for automating the entire process. A simulation model for anemia detection using RBC counting algorithm is presented in this paper. Both Circular Hough Transform and Connected Component Labelling are implemented for counting the number of RBCs and the results are compared. Watershed transform to separate overlapping blood cells is also presented. Error analysis before and after Watershed transform and parameters like segmentation accuracy, sensitivity and specificity are also included in this paper. © 2017 IEEE.
cited By 0; Conference of 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2017 ; Conference Date: 6 July 2017 Through 7 July 2017; Conference Code:136091
V. Aparna, Sarath, T. V., and Dr. K. I. Ramachandran, “Simulation model for anemia detection using RBC counting algorithms and Watershed transform”, in 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2017, 2018, vol. 2018-January, pp. 284-291.