An Achromatic Background Filter for Cytological Image Analysis
Resumo
In this work we evaluated an algorithm for filtering the achromatic background of colored cytological images. This algorithm makes use of an Isotropic White Locus Chromaticity Diagram, where the white region is selected by polar coordinates in the 1931 Chromaticity Diagram. The potential for application as a background filter is analyzed through applications to cytological images stained with the Papanicolaou method.
Referências
Bibbo, M. (1997) Comprehensive Cytophatology, Elsevier.
Bonventi Juniorr., W., Isotani, S. and Albuquerque, A. R. P. L. (1994) “A method for image background filtering of colored images using elliptical coordinates”. In Optical Methods in Biomedical and Environmental Sciences, 3, pages 75-78, Elsevier.
Bonventi Junior., W. and Isotani, S. (2007) “Segmentação de imagens histológicas hepáticas por agrupamentos nebulosos de cores”. In Proc. of III Simpósio de Instrumentação e Imagens Médicas, pages 1-4, São Carlos, Brasil.
Chen, T. K., Lu, Y. (2002) Color image segmentation-an innovative approach. In Pattern Recognition, 35(2), 395-405.
Cheng, H. D., Jiang, X. H., Sun Y., Wang, J. (2001) Color Image Segmentation. In Advances and Prospects, Pattern Recognition, 34(12), 2259-2281.
Cheng, S. -C., Yang, C. -K. (2001) “A fast and novel technique for color quantization using reduction of color space dimensionality”. In Pattern Recognition Letters, 22(8), 845-856.
Dong, G. and Xie, M. (2005) “Color Clustering and Learning for Image Segmentation Based on Neural Networks”. In IEEE Transactions on Neural Networks, 16 (4), 925-936.
Han, J., Ma, K. -K. (2002) “Fuzzy color histogram and its use in color image retrieval”. In IEEE Transactions on Image Processing, 11(8), 944-952.
Isotani, S., Brasil Filho, N., Sakai, Y. I., Albuquerque, A. R. P. L. (2007) “A system for the determination of image density and morphometry developed for the analysis of malignant nuclei”. In Proc. Twentieth IEEE International Symposium on Computer-Based Medical Systems, pages 263-267, Maribor, Eslovenia.
Isotani, S., Sakai, Y. I., Capeli, O. M., Sakai, A. T., Pereira, S. M. M., Namiyama, G. M., Maeda, M. Y. S., Bonventi-Junior., W., Albuquerque, A. R. P. L. (2008) “A new toll for the analysis of color in Spcim applied to the exam of Papanicolaou”. In Proc. Simpósio Intercâmbio Brasil-Japão, pages 1-3, São Paulo, Brasil.
Lucchese, L., Mitra, S.K. (2004) “A new class of chromatic filters for color image processing. theory and applications”. In IEEE Transactions on Image Processing, 13(4), 534-548.
Matalka, I. I., Al-Jarrah, O. M., Manasrah, T. M. (2006) “Quantitative assessment of liver fibrosis: a novel automated image analysis method”. In Liver International, 26, 1054-1064.
Munoz, X., Freixenet, J., Cufi, X., Marti, J. (2003) “Strategies for image segmentation combining region and boundary information”. In Pattern Recognition Letters, 24 (1), 375-392.
Sakai, Y. I., Sakai, A. T., Isotani, S., Cavaliere, M. J., de Almeida, L. V. and Calore, E. E. (2001) “Morphometric Evaluation of Nucleolar Organizer Regions in Cervical Intraepithelial Neoplasia”. In Pathology Research and Practice, 197, 189-192.
Stenkvist, B., Westman-Naeser, S., Holmquist, J., Nordim, B., Bengtsson, E. and Vegelius, J. (1978) “Computerized nuclear morphometry as an objective method for characterizing human cancer cell populations”. In Cancer Research, 38, 4688-4697.
Tanano, H., Hasegawa, T., Kimura, T., Sasaki, T., Kawahara, H., Kubota, A. and Okada, A. (2003) “Proposal of fibrosis index using image analyzer as a quantitative histological evaluation of liver fibrosis in biliary atresia”. In Pediatric Surgery International, 19, 52-56.
Underwood, R. A., Gibran, N. S., Muffley, L. A., Usui, M. L. and Olerud, J. E. (2001) “Color subtractive-Computer assisted image analysis for quantification of cutaneous nerves”. In Journal of Histochemistry and Cytochemistry, 49(10), 1285-1291.
Vandenbroucke, N., Macaire, L., Postaire. J. G. (2003) “Color image segmentation by pixel classification in an adapted hybrid color space”. In Application to soccer image analysis. Computer Vision and Image Understanding, 90(2), 190-216
Wied, G L, Bartels, P H, Bibbo, M. and Dytch, H. E. (1989). In Human Pathology, 20, 549-571.
Wyszecki, G. and Stiles, W. S. (1982) Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd ed., John Wiley and Sons.
Bonventi Juniorr., W., Isotani, S. and Albuquerque, A. R. P. L. (1994) “A method for image background filtering of colored images using elliptical coordinates”. In Optical Methods in Biomedical and Environmental Sciences, 3, pages 75-78, Elsevier.
Bonventi Junior., W. and Isotani, S. (2007) “Segmentação de imagens histológicas hepáticas por agrupamentos nebulosos de cores”. In Proc. of III Simpósio de Instrumentação e Imagens Médicas, pages 1-4, São Carlos, Brasil.
Chen, T. K., Lu, Y. (2002) Color image segmentation-an innovative approach. In Pattern Recognition, 35(2), 395-405.
Cheng, H. D., Jiang, X. H., Sun Y., Wang, J. (2001) Color Image Segmentation. In Advances and Prospects, Pattern Recognition, 34(12), 2259-2281.
Cheng, S. -C., Yang, C. -K. (2001) “A fast and novel technique for color quantization using reduction of color space dimensionality”. In Pattern Recognition Letters, 22(8), 845-856.
Dong, G. and Xie, M. (2005) “Color Clustering and Learning for Image Segmentation Based on Neural Networks”. In IEEE Transactions on Neural Networks, 16 (4), 925-936.
Han, J., Ma, K. -K. (2002) “Fuzzy color histogram and its use in color image retrieval”. In IEEE Transactions on Image Processing, 11(8), 944-952.
Isotani, S., Brasil Filho, N., Sakai, Y. I., Albuquerque, A. R. P. L. (2007) “A system for the determination of image density and morphometry developed for the analysis of malignant nuclei”. In Proc. Twentieth IEEE International Symposium on Computer-Based Medical Systems, pages 263-267, Maribor, Eslovenia.
Isotani, S., Sakai, Y. I., Capeli, O. M., Sakai, A. T., Pereira, S. M. M., Namiyama, G. M., Maeda, M. Y. S., Bonventi-Junior., W., Albuquerque, A. R. P. L. (2008) “A new toll for the analysis of color in Spcim applied to the exam of Papanicolaou”. In Proc. Simpósio Intercâmbio Brasil-Japão, pages 1-3, São Paulo, Brasil.
Lucchese, L., Mitra, S.K. (2004) “A new class of chromatic filters for color image processing. theory and applications”. In IEEE Transactions on Image Processing, 13(4), 534-548.
Matalka, I. I., Al-Jarrah, O. M., Manasrah, T. M. (2006) “Quantitative assessment of liver fibrosis: a novel automated image analysis method”. In Liver International, 26, 1054-1064.
Munoz, X., Freixenet, J., Cufi, X., Marti, J. (2003) “Strategies for image segmentation combining region and boundary information”. In Pattern Recognition Letters, 24 (1), 375-392.
Sakai, Y. I., Sakai, A. T., Isotani, S., Cavaliere, M. J., de Almeida, L. V. and Calore, E. E. (2001) “Morphometric Evaluation of Nucleolar Organizer Regions in Cervical Intraepithelial Neoplasia”. In Pathology Research and Practice, 197, 189-192.
Stenkvist, B., Westman-Naeser, S., Holmquist, J., Nordim, B., Bengtsson, E. and Vegelius, J. (1978) “Computerized nuclear morphometry as an objective method for characterizing human cancer cell populations”. In Cancer Research, 38, 4688-4697.
Tanano, H., Hasegawa, T., Kimura, T., Sasaki, T., Kawahara, H., Kubota, A. and Okada, A. (2003) “Proposal of fibrosis index using image analyzer as a quantitative histological evaluation of liver fibrosis in biliary atresia”. In Pediatric Surgery International, 19, 52-56.
Underwood, R. A., Gibran, N. S., Muffley, L. A., Usui, M. L. and Olerud, J. E. (2001) “Color subtractive-Computer assisted image analysis for quantification of cutaneous nerves”. In Journal of Histochemistry and Cytochemistry, 49(10), 1285-1291.
Vandenbroucke, N., Macaire, L., Postaire. J. G. (2003) “Color image segmentation by pixel classification in an adapted hybrid color space”. In Application to soccer image analysis. Computer Vision and Image Understanding, 90(2), 190-216
Wied, G L, Bartels, P H, Bibbo, M. and Dytch, H. E. (1989). In Human Pathology, 20, 549-571.
Wyszecki, G. and Stiles, W. S. (1982) Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd ed., John Wiley and Sons.
Publicado
20/07/2009
Como Citar
ISOTANI, Sadao; BONVENTI JR., Waldemar.
An Achromatic Background Filter for Cytological Image Analysis. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 9. , 2009, Bento Gonçalves/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2009
.
p. 2011-2014.
ISSN 2763-8952.
