Comparison of Segmentation Framework on Digital Microscope Images for Acute Lymphoblastic Leukemia Diagnosis Using RGB and HSV Color Spaces
Image segmentation process is considered the most essential step in image analysis especially in the medical field. In this paper, the color segmentation for acute lymphoblastic leukemia images (ALL) is applied to segment each leukemia image into two clearly defined regions: blasts and background. The ALL segmentation process is based on two different color spaces: RGB color space and HSV color space. The comparison performance between the segmentation methods based on RGB and HSV color spaces are investigated to find the best method to segment the acute lymphoblastic leukemia images. The experimental results show that the segmentation of ALL images based on HSV color space yield better accuracy than RGB color space when compared with the manual segmentation image made by medical experts. Using HSV color space, the shape of blasts in ALL blood samples is closely preserved with segmentation accuracy over 99.00%. However, segmentation based HSV color space was chosen as it produced the highest ALL segmentation rate.
. G. C. C. Lim, Overview of Cancer in Malaysia. Japanese Journal of Clinical Oncology, Department of Radiotherapy and Oncology, Hospital Kuala Lumpur, Kuala Lumpur, Malaysia, 2002.
. P. Taylor, Invited review: computer aids for decision-making in diagnostic radiology - a literature review. Brit. J. Radiol..,1995. 68:945–957.
. V.S. Khoo, et al, Magnetic resonance imaging (MRI): considerations and applications in radiotheraphy treatment planning. Radiother. Oncol., 1997. 42:1–15.
. Q. Liao, Y. Deng, An Accurate Segmentation Method for White Blood Cell Images. In IEEE International Symposium on Biomedical Imaging,2002.pp.245-248.
. V. Piuri, F. Scotti, Morphology Classification of Blood Leucocytes by Microscope Images. In IEEE International Conference on Computational Intelligence International Conference on Image, Speech and Signal Analysis, 2004. pp. 530–533.
. N. Venkateswaran, Y. V. Ramana Rao, K-means Clustering Based Image Compression in Wavelet Domain. Journal of Information Technology:, 2007. 148-153.
. S. Mao-jun, et al, A New Method for Blood Cell Image Segmentation and Counting Based on PCNN and Autowave. in ISCCSP, 2008. Malta.
. Aimi Salihah , A.N, M.Y.Mashor , Nor Hazlyna Harun, Colour Image Enhancement Techniques for Acute Leukemia Blood Cell Morphological Features. IEEE, 2010. pp.3677-3682.
. S. Mohapatra and D. Patra, Automated Cell Nucleus Segmentation and Acute Leukemia Detection in Blood Microscopic Images. in International Conference On Systems In Medecine and Biology ,2010. India.
. N. H. A. Halim, et al, Nucleus segmentation technique for acute leukemia. In Proceedings of the IEEE 7th International Colloquium on Signal Processing and Its Applications, 2011. (CSPA ’11) pp. 192–197.
. K.A. Eldahshan, et al, Segmentation Framework on Digital Microscope Images for Acute Lymphoblastic Leukemia Diagnosis based on HSV Color Space. International Journal of Computer Applications, 2014. 90(7): 2014.48-51.
. R. Donida Labati, V. Piuri, F. Scotti, ALL-IDB: the Acute Lymphoblastic Leukemia Image DataBase for image processing., 2011.
. I. Attas, J.Belward, A variational approach to the radiometric enhancement of digital imagery. IEEE Trans, Image Process, 1995. 4(6) 845-849.
. N.R.Mokhtar, et al, Contrast Enhancement of Acute Leukemia Images Using Local and Global Contrast Stretching Algorithms. ICPE,2008.
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