Abstract
Malaria is a mosquito-borne infectious disease caused by the parasite Plasmodium, which requires accurate and early diagnosis for effective containment. In order to diagnose malaria in a patient, timely detection of malaria parasites in blood smear images is vital. The traditional methods are time–consuming, tedious and the quality of detection is highly subjective to the individual who performs the analysis. These results can clearly be improved upon by using image processing techniques. The malaria parasite appears in four stages, namely the ring, trophozoite, schizont, and gametocyte. The ring and the gametocyte stage are the ones seen in a peripheral blood smear and hence detecting these two stages, would help in the accurate diagnosis of malaria. The proposed work aims at automating the analysis of the blood smear images using appropriate segmentation techniques, thereby detecting infected red blood cells as well as the gametocytes found in the blood.
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References
Sheeba, F., Thomas, Hannah, M.T.T., Mammen. J.J.: Segmentation and Reversible Watermarking of Peripheral Blood Smear Images. Proc. of the IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 1373-6.IEEE BIC-TA (2010).
Sheeba, F., Thamburaj. R,, J.J. Mammen, Hannah.M.T.T., Nagar,A.K.: White Blood Cell Segmentation and Watermarking. Proc. of the IASTED International Symposia Imaging and Signal Processing in Healthcare and Technology, Washington DC, USA. ISPHT (2011)
Sheeba, F., Thamburaj, R., Nagar, A.K., Mammen, J.J.: Segmentation of Peripheral Blood Smear Images using Tissue-like P Systems. The 6th International Conference on Bio-Inspired Computing pp. 257-261. BICTA (2011).
Anggraini, D., Nugroho, A.S., Pratama, C., Rozi, I.E., Iskandar, A.A., Hartono, R.N.: Automated Status Identification of Microscopic Images Obtained from Malaria Thin Blood Smears. International Conference on Electrical Engineering and Informatics. 1-6. ICEEI (2011).
Selena W.S. et al, Malaria Count.: An image analysis-based program for the accurate determination of parasitemia. Journal of Microbiological Methods. Elsevier (2006). doi:10.1016/j.mimet.2006.05.017
Tek, F.B., Dempsterb, A.G., Kale, I.: Computer Vision for Microscopy Diagnosis of Malaria. Malaria Journal. 8:153. 2009. doi:10.1186/1475-2875-8-153
Tek, F.B., Dempsterb, A.G., Kale, I.: Malaria Parasite Detection in Peripheral Blood Images. In: British Machine Vision Conference 347-356. BMVC (2006).
Premaratne, S.P., Karunaweera, N.D., Fernando, S., Perera, W.S.R., Rajapaksha, R.P.A. : A Neural Network Architecture for Automated Recognition of Intracellular Malaria Parasites in Stained Blood Films, http://journalogy.net/Publication/10403644
Hirimutugoda,Y.M, Wijayarathna, G. : Image Analysis System for Detection of Red Cell Disorders Using Artificial Neural Networks, Journal of Bio-Medical Informatics. 1(1): 35-42. (2010)
Halim, S., Bretschneider, T.R., Yikun Li., Preiser, P.R., Kuss, C.: Estimating Malaria Parasitaemia from Blood Smear Images. 9th International Conference on Control, Automation, Robotics and Vision. 1-6. ICARCV (2006).
Makkapati, V.V., Rao R.M..: Segmentation of Malaria Parasites in Peripheral Blood Smear Images. In: IEEE Conf. on Acoustics, Speech and Signal Processing 1361-1364. ICASSP (2009).
Gonzalez, R.C., Woods, R.E.: Digital Image Processing 3ed. by Prentice Hall. (eds). (2008).
Gonzalez, R.C., Woods, R.E., Eddins, S.L.: Digital Image Processing using Matlab. ed, by Pearson Education.(2009).
Acknowledgments
The authors would like to thank the Centre for Applicable Mathematics and Systems Science (CAMSS), Department of Computer Science, Liverpool Hope University, UK for the support and funding towards this project work and the Department of Pathology, CMC, Vellore, India for providing them with sample images for the study. The authors also thank Miss Maqlin P. and Dickson Jebaraj, Madras Christian College, Chennai, for their contribution towards the development of the system that performs automatic segmentation of malaria parasites in blood smear images.
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Sheeba, F., Thamburaj, R., Mammen, J.J., Nagar, A.K. (2013). Detection of Plasmodium Falciparum in Peripheral Blood Smear Images. In: Bansal, J., Singh, P., Deep, K., Pant, M., Nagar, A. (eds) Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012). Advances in Intelligent Systems and Computing, vol 202. Springer, India. https://doi.org/10.1007/978-81-322-1041-2_25
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DOI: https://doi.org/10.1007/978-81-322-1041-2_25
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