1. THEJASHWINI M, PADMA M C. Counting of RBC’s and WBC’s using image processing technique[J]. International journal on recent and innovation trends in computing and communication, 2015, 3(5): 2948–2953.
2. OTHMAN M Z, MOHAMMED T S, ALI A B. Neural network classification of white blood cell using microscopic images[J]. International journal of advanced computer science and applications, 2017, 8(5): 99–104.
3. KHAN S, KHAN A, KHATTAK F S, et al. An accurate and cost effective approach to blood cell count[J]. International journal of computer applications, 2012, 50(1): 975–8887.
4. MAZALAN S M, MAHMOOD N H, RAZAK M A A. Automated red blood cells counting in peripheral blood smear image using circular Hough transform[C]//2013 1st International Conference on Artificial Intelligence, Modelling and Simulation, December 3–5, 2013, Kota Kinabalu, Malaysia. New York: IEEE, 2013: 320–324.
5. AlOMARI Y M, SHEIKH ABDULLAH SNH, ZAHARATUL AZMA R, et al. Automatic detection and quantification of WBCs and RBCs using iterative structured circle detection algorithm[J]. Computational and mathematical methods in medicine, 2014, 2014(8): 979302.