Segmentation of Malaria Parasite Candidate from Thickblood Smear Microscopic Images using Watershed and Adaptive Thresholding
WHO, World Malaria report 2014, Switzerland [Online]. Available: http: //www.who.int/malaria/publications/world_malaria_report_2014 /en/
WHO, Basic Malaria Microscopy, Switzerland, 2010.
D. Syafruddin, P.B Asih, I.E.P. Rozi, K. Chand, and S. Wangsamuda. Diagnosis Mikroskopik Malaria. Lembaga Biologi Molekuler Eijkman, 2010.
H. Yang and N. Ahuja, “Automatic segmentation of granular objects in images: Combining local density clustering and gradient-barrier watershed”, Pattern Recognition vol. 47, pp. 2266–2279, 2014.
E. A. Mohammed, M. A. Mohamed, C. Naugler, and B. H. Far, “Chronic Lymphocytic Leukemia Cell Segmentation from Microscopic Blood Images Using Watershed Algorithm and Optimal Thresholding”, in 26th IEEE Canadian Conference Of Electrical And Computer Engineering (CCECE), 2013.
L. Xu, H. Lu, and M. Zhang, “Automatic segmentation of clustered quantum dots based on improved watershed transformation”, Digital Signal Processing, vol. 34, pp. 108–115, 2014.
A. Mouelhia, M. Sayadia, F. Fnaiecha, K. Mradb, and K. B. Romdhaneb, “Automatic image segmentation of nuclear stained breast tissue sections using color active contour model and an improved watershed method”, Biomedical Signal Processing and Control, vol. 8, pp. 421– 436, 2013.
S Kaewkamnerd, et al., “Detection and Classification Device for Malaria Parasites in Thick-Blood Films”, in The 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, September, 2011.
M. Elter, E. Haßlmeyer, and T. Zerfa, “ Detection of malaria parasites in thick blood films”, in 33rd Annual International Conference of the IEEE EMBS, Boston, August 2011.
J. E.Arco, J. M. Górriz, J. Ramírez, I. Álvarez, and C. G. Puntonet, “Digital Image Analysis for Automatic Enumeration of Malaria Parasites using Morphological Operations”, Expert Systems with Applications, vol. 42, pp. 3041–3047, 2015.
E. H. Adelson, C. H. Anderson, J. R. Bergen, P. J. Burt, and J. M. Ogden Pyramid methods in image processing. RCA Engineer, 1984.
R. C. Gonzales and R. E. Woods, Digital Image Processing – Third Edition. Prentice Hall. Upper Saddle River, New Jersey, 2010.
M. Ghosh, C. Chakraborty, A. Konar, and K. R.Ray,” Development of hedge operator based fuzzy divergence measure and its aplication in segmentation of cronic myelogenous leukocytes from microscopic image of periperal blood smear”, Micron, vol. 57 pp. 41 – 55, 2014.
N. V. Lopes, P. A. Mogadouro, H. Bustince, and P. Melo-pinto, “Automatic Histogram Threshold Using Fuzzy Measures,” IEEE Trans. IMAGE Process., vol. 19, no. 1, pp. 199–204, 2010.
G. Q. O. Pratamasunu, A. Z. Arifin, D. A. Navastara, A. Y. Wijaya, and W. N. Khotimah, “Image Thresholding Based on Index of Fuzziness and Fuzzy Similarity Measure,” in IEEE 8th International Workshop on Computational Intelligence and Applications, 2015.
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