Nucleus and cytoplast contour detector from a cervical smear image

Expert Systems with Applications

Volumn 39, Issue 1, 2012, Pages 154-161

  Pai, Pei Yan ^a   Chang, Chin Chen ^b   Chan, Yung Kuan ^c  

^a ASIA UNIVERSITY   (Taiwan)

^b FENG CHIA UNIVERSITY   (Taiwan)

^c NATIONAL CHUNG HSING UNIVERSITY   (Taiwan)

Author keywords

Cervical cancer; Cervical smear screening; Image segmentation; Thresholding

Indexed keywords

CERVICAL CANCERS; CONTOUR MODELS; EDGE ENHANCEMENTS; GRADIENT VECTORS; THRESHOLDING;

CELLS; DETECTORS;

IMAGE SEGMENTATION;

EID: 81855218755     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.06.034     Document Type: Article

References (21)

1. C.W. Boast, and P. Baveye Alleviation of an indeterminacy problem affecting two classical iterative image thresholding algorithm International Journal of Pattern Recognition and Artificial Intelligence 20 1 2006 1 14
2. Y. Boykov, and G. Funka-Lea Graph cuts and efficient n - d image segmentation International Journal of Computer Vision 70 2 2006 109 131
3. Boykov, Y.; & Jolly, M. P. (2001). Interactive graph cuts for optimal boundary & region segmentation of object in N-D images. In Proceeding of international Conference on Computer Vision I (pp. 105-112).
4. J. Canny A computational stage to edge detection IEEE Transactions on Pattern Analysis and Machine Intelligence 8 6 1986 679 698
5. T.F. Chan, and L.A. Vese Active contours without edges IEEE Transactions on Image Processing 10 2 2001 266 277
6. E. Davies Machine vision: Theory, algorithms and practicalities 1990 Academic Press
7. W.J. Frable Needle aspiration biopsy of pulmonary tumors Seminars in Respiratory Medicine 4 2 1982 161 169
8. Z. Hou, Q. Hu, and W.L. Nowinski On minimum variance thresholding Pattern Recognition Letters 27 14 2006 1732 1743
9. M. Kass, A. Witkin, and D. Terzopoulos Snakes: Active contour models International Journal of Computer Vision 1 4 1998 321 331
10. N.A. Mat-Isa, M.Y. Mashor, and N.H. Othman Seeded region growing features extraction algorithm: Its potential use in improving screening for cervical cancer International Journal of the Computer, The Internet and Management 13 1 2005 61 70
11. N. Otsu A threshold selection method from gray-level histograms IEEE Transactions of Systems, Man, and Cybernetics 9 1 1979 62 66
12. P.K. Sahoo, S. Soltani, A.K. Wong, and Y.C. Chan A survey of thresholding techniques Computer Vision, Graphics and Image Processing 41 2 1988 233 260
13. M. Sezgin, and B. Sanlur Survey over image thresholding techniques and quantitative performance evaluation Journal of Electronic Imaging 13 1 2004 146 165
14. F.Y. Shih, and K. Zhang Efficient contour detection based on improved snake model International Journal of Pattern Recognition and Artificial Intelligence 18 2 2004 197 209
15. M.H. Tsai, M.H. Wang, T.Y. Chang, P.Y. Pai, Y.K. Chan, and J.M. Chen An adaptable threshold decision method International Journal of Innovative Computing Information and Control 6 5 2010 2285 2300
16. Wallker, R.F. 1997. Adaptive multi-scale texture analysis with application to automated cytology, Dissertation, Department of Electrical and Computer Engineering, University of Queensland
17. H.S. Wu, J. Gil, and J. Barba Optimal segmentation of cell images IEE Proceedings Vision, Image & Signal Processing 145 1 1998 50 56
18. C. Xu, and L. Prince Snakes, shapes, and gradient vector flow IEEE Transactions on Image Processing 7 3 1998 359 369
19. W. Xu, S. Xia, H. Duan, and M. Xiao Segmentation of mass in mammograms using a novel intelligent algorithm International Journal of Pattern Recognition and Artificial Intelligence 20 2 2006 255 270
20. S.F. Yang-Mao, Y.K. Chan, and Y.P. Chu Edge enhancement nucleus and cytoplast contour detector of cervical smear images IEEE Transactions on Systems, Man, and Cybernetics - Part B 38 2 2008 353 366
21. Women's Health Report FY 2005-2006, National cancer institute, 2007. (Feb.; 2007).