Counting of RBCs and WBCs in noisy normal blood smear microscopic images

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 7963, Issue , 2011, Pages

  Habibzadeh, M ^a   Krzyzak, A ^a   Fevens, T ^a   Sadr, A ^b  

^a Gina Cody School of Engineering and Computer Science   (Canada)

^b SHARIF UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

active contours; binarization; CBC; Denoising; RBC; watershed; WBC

Indexed keywords

ACTIVE CONTOURS; BINARIZATION; CBC; DE-NOISING; RBC; WBC;

ALGORITHMS; CELLS; COMPUTER AIDED DIAGNOSIS; COMPUTER PERIPHERAL EQUIPMENT; IMAGE SEGMENTATION; LANDFORMS; MEDICAL IMAGING; MERGING; NOISE POLLUTION CONTROL; PROFITABILITY; WATERSHEDS;

BLOOD;

EID: 79955752684     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.878748     Document Type: Conference Paper

References (52)

1. S. M. Lewis, B. J. Bain, I. Bates, Dacie, Lewis "chapter 5:Blood cell morphology in health and disease" practical hematology, 10th ed. Philadelphia: Churchill Livingstone Elsevier, pp. 103,2006
2. S. M. Lewis, B. J. Bain, and I. Bates, Dacie and Lewis," chapter 5: Blood cell morphology in health and disease" practical hematology, 10th ed. Philadelphia: Churchill Livingstone Elsevier, pp. 80,2006.
3. Ramoser, H.; Laurain, V.; Bischof, H.; Ecker, R.;, Leukocyte segmentation and classification in bloodsmear images, Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the, vol., no., pp.3371-3374, 17-18 Jan. 2006
4. Joseph J. Schall, Professor. Ph.D, The University of Texas at Austin, "Making and Staining a Blood Smear". uvm.edu. [Online].Available:http: //www.uvm.edu/~jschall/pdfs/techniques/bloodsmears.pdf. [Accessed: August. 06, 2010].
5. « Giemsa stain ».med-chem.com [Online]. Available: http://med-chem.com/procedures/Giemsabsp.pdf. [Accessed: august. 06, 2010].
6. Bentley, S. & Lewis, S. The use of an image analyzing computer for the quantification of red cell morphological characteristics. British Journal of Hematology 29, 81-88. 1975
7. Rowan, R. Automated examination of the peripheral blood smear, in 'Automation and quality assurance in hematology', Blackwell Scientific, Oxford, chapter 5, pp. 129-177.1986
8. Martelli, A. An application of heuristic search methods to edge and contour detection Communications of the ACM 19(2), 73-83.1976
9. Pope, D., Parker, D., Clayton, P. & Gustafson, D. Left ventricular border recognition using a dynamic search algorithm. Radiology 155(2), 513-518.1985 (Pubitemid 15033149)
10. Fleagle, S.R.; Johnson, M.R.; Wilbricht, C.J.; Skorton, D.J.; Wilson, R.F.; White, C.W.; Marcus, M.L.; Collins, S.M.; Automated analysis of coronary arterial morphology in cineangiograms: geometric and physiologic validation in humans, IEEE Transactions on Medical Imaging, vol.8, no.4, pp.387-400, Dec 1989
11. Fleagle,S., Thedens,D., Ehrhardt,J., Scholz,T.& Skorton,D. Automated identification of left ventricular borders from spin-echo magnetic resonance images. Investigative Radiology 26(4),295-303.1991
12. Adjouadi,M.,Fernandez,N.An orientation-independent imaging technique for the classification of blood cells. Particle & Particle Systems Characterization 18(2), 91-98.2001 (Pubitemid 32813191)
13. Di Rubeto, C.; Dempster, A.; Khan, S.; Jarra, B.; Segmentation of blood images using morphological operators, Pattern Recognition, 2000. Proceedings. 15th International Conference on, vol.3, no., pp.397-400, 2000
14. Beucher, S. Watersheds of functions and picture segmentation, Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '82., vol.7, no., pp. 1928-1931, May 1982
15. Beucher,S. The watershed transformation applied to image segmentation. Proceedings of the 10th Pfefferkorn conference on Signal and Image Processing in Microscopy and Micro analysis, Cambridge, UK, pp 299-314. September 1991
16. M.Couprie, G. Bertrand. Topological grayscale watershed transformation. Proc. SPIE Vision Geometry V, vol. 3168, pp.136-146. 1997
17. Gauch, J.M.; Image segmentation and analysis via multi scale gradient watershed hierarchies, Image Processing, IEEE Transactions on, vol.8, no.1, pp.69-79, Jan 1999
18. C. De Roover, A. Herbulot, A. Gouze, E. Debreuve, M. Barlaud, and B. Macq, Multimodal segmentation combining active contours and watersheds, in Proceedings of the 13th European Signal Processing Conference (EUSIPCO '05), Antalya, Turkey, September 2005.
19. Kass, M., Witkin, A. & Terzopoulos, D. Snakes: Active contour models. International Journal of Computer Vision 4, pp:321-331.1988
20. Leznray 0, Elmoataz A, Cardot H, Gougeon G, Lecluse M, Elie H, Revenu M. Segmentation of cytological images using color and mathematical morphology. European Congress of Stereology, 18(1): 1-14, 1999
21. Ongun, G.; Halici, U.; Leblebicioglu, K.; Atalay, V.; Beksac, M.; Beksac, S.; An automated differential blood count system, Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE, vol.3, no., pp. 2583-2586, 2001 (Pubitemid 35389170)
22. Ongun, G., Halici, U., Leblebicioglu, K., Atalay, V.Beksac, S. and Beksac, M. Automated contour detection in blood cell images by an efficient snake algorithm. Nonlinear Analysis-Theory Methods & Applications 47(9), 5839-5847.2001 (Pubitemid 32934770)
23. Ongun G, Halici U, Leblebicioglu K, Atalay V, Beksac M, Beksac S. Feature extraction and classification of blood cells for an automated differential blood count system. Proc. IJCNN, 4: 2461-2466. 2001 (Pubitemid 32794696)
24. D. Comaniciu and P. Meer. Cell image segmentation for diagnostic pathology. In J. S. Suri, S. K. Setarehdan, and S. Singh, editors, advanced algorithmic approaches to medical image segmentation: state-of-the-art application in cardiology, neurology, mammography and pathology, pages 541-558. Springer. 2001
25. Kumar B R, Joseph D K, Sreenivas T V. Teager energy based blood cell segmentation. International Conference on Digital Signal Processing, 2: 619-622. 2002
26. N. Sinha and A. G. Ramakrishnan. Automation of differential blood count. In Proc. Conf. on Convergent Technologies for Asia-Pacific Region, volume 2, pages 547-551. 2003
27. K. Jiang, Q.-M. Liao and S.-Y. Dai. A novel white blood cell segmentation scheme using scale space filtering and watershed clustering. In Proc. Int. Conf. on Machine Learning and Cybernetics, volume 5, pages 2820-2825.2003
28. Theerapattanakul, J.; Plodpai, J.; Pintavirooj, C.;, An efficient method for segmentation step of automated white blood cell classifications, TENCON 2004. 2004 IEEE Region 10 Conference, vol.A, no., pp. 191-194 Vol. 1, 21-24 Nov. 2004
29. Hamghalam, M.; Motameni, M.; Kelishomi, A.E.;, Leukocyte Segmentation in Giemsa-stained Image of Peripheral Blood Smears Based on Active Contour, 2009 International Conference on Signal Processing Systems, pp.103-106, 15-17 May 2009
30. F. Cloppet,A. Boucher. Segmentation of complex nucleus configurations in biological images. Pattern Recognition Letters, volume31, no:8,pages 755-761.2010
31. Sendur, L.; Selesnick, I.W.; Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency, Signal Processing, IEEE Transactions on, vol.50, no.11, pp. 2744-2756, Nov 2002 (Pubitemid 35312118)
32. Sendur, L.; Selesnick, I.W.;A bivariate shrinkage function for wavelet-based denoising, Acoustics, Speech, and Signal Processing, 2002. Proceedings. (ICASSP '02). IEEE International Conference on, vol.2, no., pp.1261-1264, 2002
33. Lim, Jae S., Two-Dimensional Signal and Image Processing, Englewood Cliffs, NJ, Prentice Hall, pp. 469-476, 1990.
34. Vinh Hong1, Henryk Palus2, and Dietrich Paulus. Edge Preserving Filters on Color Images. Springer-Verlag Berlin Heidelberg, vol.3039 no. pp.34-40, 2004.
35. Babic, Z.V.; Mandic, D.P.; An efficient noise removal and edge preserving convolution filter, Telecommunications in Modern Satellite, Cable and Broadcasting Service, 2003. TELSIKS 2003. 6th International Conference on, vol.2, no., pp. 538-541 vol.2, 1-3 Oct. 2003
36. Nikos Nikolaou, Nikos Papamarkos. Color Reduction for Complex Document Images. International Journal of Imaging Systems and Technology, Vol. 19 (1) pp. 14-26, 2009.
37. Tomasi, C.; Manduchi, R.; bilateral filtering for gray and color images, Computer Vision, 1998. Sixth International Conference on, vol., no., pp.839-846, 4-7 Jan 1998
38. Papari, G.; Petkov, N.; Campisi, P.; Artistic Edge and Corner Enhancing Smoothing, Image Processing, IEEE Transactions on, vol.16, no.10, pp.2449-2462, Oct. 2007
39. "Connective tissue-blood & blood forming tissues, http://www.rutgers.edu/,[online].available:http://lifesci.rutgers.edu/~babiarz/ bloodtx.htm. [Accessed: August. 06, 2010].
40. Ntogas Nikolaos, Ventzas Dimitrios, A binarization algorithm for historical manuscripts, 12th WSEAS International Conference on communications, Heraklion, Greece, Pages: 41-51, 2008
41. Sauvola, M. Pietikainen. Adaptive document image binarization.Elsevier The journal of the pattern recognition society. Vol.33, Issue 2, pp:225-236, February 2000
42. Nobuyuki Otsu, A Threshold Selection Method from Gray-Level Histograms, Systems, Man and Cybernetics, IEEE Transactions on, vol.9, no.1, pp.62-66, Jan. 1979
43. Bergen, Tobias; Steckhan, Dirk; Wittenberg, Thomas; Zerfass, Thorsten; Segmentation of leukocytes and erythrocytes in blood smear images, Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE, vol., no., pp.3075-3078, 20-25 Aug. 2008
44. Canny, John,A Computational Approach to Edge Detection, Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.PAMI-8, no.6, pp.679-698, Nov. 1986
45. S. M. Lewis, B. J. Bain, and I. Bates, Dacie and Lewis, chapter 5:Blood cell morphology in health and disease practical haematology, 10th ed. Philadelphia: Churchill Livingstone Elsevier, pp. 107-110, 2006
46. Newland J. The peripheral blood smear. Goldman L,Ausiello D, eds. Cecil Medicine. 23rd ed. Philadelphia, Pa: Saunders Elsevier, chap 161, 2007.
47. Luc Vincent. Fast Opening Functions and Morphological Granulometries. Image Algebra and Morphological Image Processing, SPIE Vol. 2300, pp. 253-267, July 1994
48. Chan, T.F.; Vese, L.A.;, Active contours without edges, Image Processing, IEEE Transactions on, vol.10, no.2, pp.266-277, Feb 2001
49. Yung-Chieh Lin; Yu-Pao Tsai; Yi-Ping Hung; Zen-Chung Shih; Comparison between immersion-based and toboggan-based watershed image segmentation, Image Processing, IEEE Transactions on, vol.15, no.3, pp.632-640, March 2006 (Pubitemid 43257562)
50. Von Wegner, F.; Both, M.; Fink, R.H.A.; Friedrich, O.;Fast XYT Imaging of Elementary Calcium Release Events in Muscle With Multifocal Multiphoton Microscopy and Wavelet Denoising and Detection, Medical Imaging, IEEE Transactions on, vol.26, no.7, pp.925-934, July 2007 (Pubitemid 47147240)
51. Negar M. Harandi, Saeed Sadri,Noushin A. Moghaddam, Rassul Amirfattahi. An Automated Method for Segmentation of Epithelial Cervical Cells in Images of ThinPrep. Springer Journal of medical systems. PP: 1-16, 2009
52. Cecilia Di Ruberto, Andrew Dempster, Shahid Khan, Bill Jarra. Morphological Image Processing for Evaluating Malaria Disease. Springer-Verlag Berlin Heidelberg, Volume 2059, PP: 739-748, 2001.