Abstract
The accurate count of a patient’s blood cells is vital for successful diagnosis of a plethora of diseases. Current systems deployed in Pakistan either rely on heavy and expensive machinery or is sometimes conducted manually. We propose the use of digital image processing techniques to build a cheaper alternative, that rely on digital images of blood smears, which are economical to produce, and are in fact a costless feature built-in to most existing lab microscopes. In this work, morphological image processing is deployed to segment the image and to differentiate and extract the blood cells from the plasma. The algorithm will exploit the shape and radius of blood cells for counting. After segmenting blood cells, their counting becomes a trivial task. The proposed system will be complementary to medical practitioners and provide a second opinion for their subjective diagnosis.
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References
Kasuya, H., Onda, H., Yoneyama, T., Sasaki, T., & Hori, T. (2003). Bedside monitoring of circulating blood volume after subarachnoid hemorrhage stroke. Stroke, 34(4), 956–960.
Visconte, V., Tabarroki, A., Gerace, C., Al-Issa, K., Hsi, E. D., Silver, B. J., Lichtin, A. E., & Tiu, R. V. (2014). Somatic mutations in splicing factor 3b, subunit 1 (SF3B1) are a useful biomarker differentiate between clonal and non-clonal causes of sideroblastic anemia. Blood, 124, 5597.
Smith, M. T. (1996). The mechanism of benzene-induced leukemia: A hypothesis and speculations on the causes of leukemia. Environmental Health Perspectives, 104(Suppl 6), S1219–S1225. https://doi.org/10.1289/ehp.961041219.
Audard, V., Bartolucci, P., & Stehlé, T. (2017). Sickle cell disease and albuminuria: recent advances in our understanding of sickle cell nephropathy. Clinical Kidney Journal, 10(4), 475–478.
Aroon Kamath, M. (2014). Automated blood-cell analyzers. Can you count on them to count well?. Doctors Lounge Website. Available at: https://www.doctorslounge.com/index.php/blogs/page/17172
Mahmood, N. H., & Mansor, M. A. (2012). Red blood cells estimation using Hough transform technique. Signal & Image Processing, 3(2), 53.
Sharif, J. M., Miswan, M. F., Ngadi, M. A., Salam, M. S. H., & Bin Abdul Jamil, M. M. (2012). Red blood cell segmentation using masking and watershed algorithm: A preliminary study. In Biomedical Engineering (ICoBE), 2012 International Conference on (pp. 258-262). IEEE.
Bala, S., & Doegar, A. (2015). Automatic detection of sickle cell in red blood cell using watershed segmentation. International Journal of Advanced Research in Computer and Communication Engineering, 4(6), 488–491.
Joost Vromen, B. M. (2009). Red blood cell segmentation from SEM images. In: Image and Vision Computing New Zealand, (2009). IVCNZ’09. 24th International Conference, New Zealand.
Damahe, L. B., Krishna, R., & Janwe, N. (2011). Segmentation based approach to detect parasites and RBCs in blood cell images. International Journal of Computer Science and Applications, 4, 71–81.
Zack, G. W., et al. (1997). Automatic measurement of sister chromatid exchange frequency. The journal of histochemistry and cytochemistry: Official Journal of the Histochemistry Society, 25(7), 741–753.
Scholz, J., Klein, M. C., Behrens, E. J., & Johansen-Berg, H. (2009). Training induces changes in white matter architecture. Nature Neuroscience, 12, 1370–1371.
Lee, D. T., & Schachter, B. J. (1980). Two algorithms for constructing a delaunay triangulation. International Journal of Computer and Information Sciences, 9(3), 219–224.
Sadeghian, F., Seman, Z., Ramli, A. R., Kahar, B. H. A., & Saripan, M. I. (2009). A framework for white blood cell segmentation in microscopic blood images using digital image processing. Biological Procedures Online, 11(1), 196.
Jiang, K., Liao, Q. M., & Dai, S. Y. (2003). A novel white blood cell segmentation scheme using scale-space filtering and watershed clustering. In Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (pp. 2820–2825). IEEE.
Torre, V., & Poggio, T. A. (1986). On edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(2), 147–163.
Acharjya, P. P., Sinha, A., Sarkar, S., Dey, S., & Ghosh, S. (2013). A new approach of watershed algorithm using distance transform applied to image segmentation. International Journal of Innovative Research in Computer and Communication Engineering, 1(2), 185–189.
Kakarla, J., & Majhi, B. (2013). A new optimal delay and energy efficient coordination algorithm for WSAN. In 2013 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) (pp. 1–6).
Francos, J. M., Meiri, A. Z., & Porat, B. (1993). A unified texture model based on a 2-D Wold-like decomposition. IEEE Transactions on Signal Processing, 41(8), 2665–2678.
Mazalan, S. M. Automated red blood cells counting in peripheral blood smear image using Circular Hough Transform. In: Artificial intelligence, modelling and simulation (AIMS), first international conference on artificial intelligence, modelling & simulation, IEEE, (2013).
Celenk, M. (1990). A color clustering technique for image segmentation. Computer Vision, Graphics, and Image Processing, 52(02), 145–170.
Tcheslavski, G. V. (n.d.). Morphological image processing: Basic algorithms. Retrieved from http://ee.lamar.edu/gleb/dip/ (7/05/2016).
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Chaudhary, A.H., Ikhlaq, J., Iftikhar, M.A., Alvi, M. (2019). Blood Cell Counting and Segmentation Using Image Processing Techniques. In: Khan, F., Jan, M., Alam, M. (eds) Applications of Intelligent Technologies in Healthcare. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-96139-2_9
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