Segmentation of Breast Cancer Fine Needle Biopsy Cytological Images

Arabas J. (2004). Lectures on Evolutionary Algorithms, WNT, Warsaw (in Polish).Search in Google Scholar

Ballard D. (1981). Generalizing the Hough transform to detect arbitrary shapes, Pattern Recognition 13(2): 111-122.10.1016/0031-3203(81)90009-1Search in Google Scholar

Blake A., Isard M. (1998). Active Contours, Springer, London.10.1007/978-1-4471-1555-7Search in Google Scholar

Boldrini J. and Costa M. (1999). An application of optimal control theory to the design of theoretical schedules of anticancer drugs, International Journal of Applied Mathematics and Computer Science 9(2): 387-399.Search in Google Scholar

Carlotto M. (1987). Histogram analysis using a scale space approach, IEEE Transactions on Pattern Analysis and Machine Intelligence 9(1): 121-129.10.1109/TPAMI.1987.4767877Search in Google Scholar

Chen C., Luo J. and Parker K. (1998). Image segmentation via adaptive K-mean clustering and knowledge-based morphological operations with biomedical applications, IEEE Transactions on Image Processing 7(12): 1673-1683.10.1109/83.730379Search in Google Scholar

Duda R. and Hart P. (1972). Use of the Hough transformation to detect lines and curves in picture, Communications of Association for Computing Machinery 15(1): 11-15.10.1145/361237.361242Search in Google Scholar

Gonzalez R. and Woods R. (2002). Digital Image Processing, Prentice Hall, Englewood Cliffs, NJ.Search in Google Scholar

Hrebień M., Nieczkowski T., Korbicz J. and Obuchowicz A. (2006). The Hough transform and the GrowCut method in segmentation of cytological images, Proceedings of the International Conference on Signal and Electronic Systems ICSES'06, Łódź Poland, pp. 367-370.Search in Google Scholar

Hrebień M. and Steć P. (2006). Fine needle biopsy material segmentation with Hough transform and active contouring technique, Journal of Medical Informatics and Technologies 10: 25-34, (in print).Search in Google Scholar

Hrebień M., Korbicz J. and Obuchowicz A. (2007). Hough transform, (1+1) search strategy and watershed algorithm in segmentation of cytological images, Proceedings of the 5th International Conference on Computer Recognition Systems CORES'07, Springer, Wrocław, pp. 550-557.Search in Google Scholar

Kass M., Witkin A. and Terauzopoulos D. (1987). Snakes: Active contour models, Proceedings of the 1st International Conference on Computer Vision, pp. 259-263.Search in Google Scholar

Kimmel M., Lachowicz M. and Świerniak A. (Eds.) (2003). Cancer growth and progression, mathematical problems and computer simulations, International Journal of Applied Mathematics and Computer Science 13(3) (Special Issue).Search in Google Scholar

Lee M. and Street W. (2000). Dynamic learning of shapes for automatic object recognition, Proceedings of the 17th Workshop Machine Learning of Spatial Knowledge, Stanford, CA, pp. 44-49.Search in Google Scholar

Madisetti V. and Williams D. (1997). The Digital Signal Processing Handbook, CRC Press, Boca Raton, FL.Search in Google Scholar

Marciniak A., Obuchowicz A., Monczak R. and Kołodziński M. (2005). Cytomorphometry of fine needle biopsy material from the breast cancer, Proceedings of the 4th International Conference on Computer Recognition Systems CORES'05, Springer, Rydzyna, Poland, pp. 603-609.Search in Google Scholar

Michalewicz Z. (1996): Genetic Algorithms + Data Structures = Evolution Programs, Springer, London.10.1007/978-3-662-03315-9Search in Google Scholar

Otsu N. (1979). A threshold selection method from grey-level histograms, IEEE Transactions on Systems, Man and Cybernetics 9(1): 62-66.10.1109/TSMC.1979.4310076Search in Google Scholar

Pena-Reyes C. and Sipper M. (1998). Envolving fuzzy rules for breast cancer diagnosis, Proceedings of the International Symposium on Nonlinear Theory and Application, Vol. 2, Polytechniques et Universitaires Romandes Press, pp. 369-372.Search in Google Scholar

Pratt W. (2001). Digital Image Processing, Wiley, New York.10.1002/0471221325Search in Google Scholar

Russ J. (1999). The Image Processing Handbook, CRC Press, Boca Raton, FL.Search in Google Scholar

Sethian J. (1999). Fast marching methods, SIAM Review 41(2): 199-235.10.1137/S0036144598347059Search in Google Scholar

Setiono R. (1996). Extracting rules from pruned neural networks for breast cancer diagnosis, Artificial Intelligence in Medicine 8(1): 37-51.10.1016/0933-3657(95)00019-4Search in Google Scholar

Steć P. and Domański M. (2005). Video frame segmentation using competitive contours, Proceedings of the 13th European Signal Processing Conference EUSIPCO'05, Antalya, Turkey, pp. 4 (CD-ROM).Search in Google Scholar

Street W. (2000). Xcyt: A system for remote cytological diagnosis and prognosis of breast cancer, in: (Jain L. (Ed.)), Soft Computing Techniques in Breast Cancer Prognosis and Diagnosis, World Scientific Publishing, Singapore, pp. 297-322.10.1142/9789812792488_0008Search in Google Scholar

Su M. and Chou C. (2001). A modified version of the K-means algorithm with a distance based on cluster symmetry, IEEE Transactions Pattern Analysis and Machine Intelligence 23(6): 674-680.10.1109/34.927466Search in Google Scholar

Świerniak A., Ledzewicz U. and Schättler H. (2003). Optimal control for a class of compartmental models in cancer chemotherapy, International Journal of Applied Mathematics and Computer Science 13(3): 357-368.Search in Google Scholar

Tadeusiewicz R. (1992). Vision Systems of Industrial Robots, WNT, Warsaw, (in Polish).Search in Google Scholar

Vezhnevets V. and Konouchine V. (2005). "GrowCut"—interactive multi-label N-D image segmentation by cellular automata, Proceedings of the 15th International Conference on Computer Graphics and Applications GraphiCon'05, Novosibirsk, Russia, pp. 150-156.Search in Google Scholar

Vincent L. and Soille P. (1991). Watersheds in digital spaces: An efficient algorithm based on immersion simulations, IEEE Transactions on Pattern Analysis and Machine Intelligence 13(6): 583-598.10.1109/34.87344Search in Google Scholar

Wolberg W., Street W. and Mangasarian O. (1993). Breast cytology diagnosis via digital image analysis, Analytical and Quantitative Cytology and Histology 15(6): 396-404.Search in Google Scholar

Zhang J. (1996). A survey on evaluation methods for image segmentation, Pattern Recognition 29(8): 1335-1346.10.1016/0031-3203(95)00169-7Search in Google Scholar

Zhou P. and Pycock D. (1997). Robust statistical models for cell image interpretation, Image and Vision Computing 15(4): 307-316.10.1016/S0262-8856(96)01129-8Search in Google Scholar

Żorski W. (2000). Image Segmentation Methods Based on the Hough Transform, Studio GiZ, Warsaw, (in Polish).Search in Google Scholar