Abstract
The advent of digital whole-slide scanners in recent years has spurred a revolution in imaging technology for histopathology. In order to encourage further interest in histopathological image analysis, we have organized a contest called “Pattern Recognition in Histopathological Image Analysis.” This contest aims to bring some of the pressing issues facing the advance of the rapidly emerging field of digital histology image analysis to the attention of the wider pattern recognition and medical image analysis communities. Two sample histopathological problems are explored: counting lymphocytes and centroblasts. The background to these problems and the evaluation methodology are discussed.
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Jemal, A., Siegel, R., Ward, E., Hao, Y., Xu, J., Murray, T., Thun, M.J.: Cancer statistics. CA Cancer J. Clin. 58(2), 71–96 (2008)
Bertucci, F., Birnbaum, D.: Reasons for breast cancer heterogeneity. J. Biol. 7(6) (2008)
van Nagell, J.R., Donaldson, E.S., Wood, E.G., Parker, J.C.: The significance of vascular invasion and lymphocytic infiltration in invasive cervical cancer. Cancer 41(1), 228–234 (1978)
Aaltomaa, S., Lipponen, P., Eskelinen, M., Kosma, V.M., Marin, S., Alhava, E., Syrjanen, K.: Lymphocyte infiltrates as a prognostic variable in female breast cancer. Eur. J. Cancer 28A(4/5), 859–864 (1992)
Alexe, G., Dalgin, G.S., Scanfeld, D., Tamayo, P., Mesirov, J.P., DeLisi, C., Harris, L., Barnard, N., Martel, M., Levine, A.J., Ganesan, S., Bhanot, G.: High expression of lymphocyte-associated genes in node negative her2+ breast cancers correlates with lower recurrence rates. Cancer Res. 67(22), 10669–10676 (2007)
Fatakdawala, H., Basavanhally, A., Xu, J., Bhanot, G., Ganesan, S., Feldman, M., Tomaszewski, J., Madabhushi, A.: Expectation Maximization Driven Geodesic Active Contour with Overlap Resolution: Lymphocyte Segmentation on Breast Cancer Histopathology. IEEE Transactions on Biomedical Engineering 57(7), 1676–1689 (2010) (PMID: 20172780)
Jaffe, E.S., Harris, N.L., Stein, H., Vardiman, J.W.: World Health Organization Classification of Tumours - Tumours of Haematopoietic and Lymphoid Tissues. IARC Press, Lyon (2001)
Gurcan, M.N., Boucheron, L., Can, A., Madabhushi, A., Rajpoot, N., Yener, B.: Histopathological Image Analysis: A review. IEEE Reviews in Biomedical Engineering 2, 147–171 (2009)
Sertel, O., Kong, J., Catalyurek, U.V., Lozanski, G., Saltz, J., Gurcan, M.N.: Histopathological image analysis using model-based intermediate representations and color texture: Follicular lymphoma grading. The Journal of Signal Processing Systems 55, 169–183 (2009)
Cooper, L., Sertel, O., Kong, J., Lozanski, G., Huang, K., Gurcan, M.N.: Feature-Based Registration of Histopathology Images with Different Stains: An Application for Computerized Follicular Lymphoma Prognosis. Computer Methods and Programs in Biomedicine 96(3), 182–192 (2009)
Sertel, O., Kong, J., Lozanski, G., Catalyurek, U., Saltz, J., Gurcan, M.N.: Computerized microscopic image analysis of follicular lymphoma. In: SPIE Medical Imaging 2008, San Diego, California, pp. 16–21 (February 2008)
Sertel, O., Kong, J., Catalyurek, U., Lozanski, G., Shanaah, A., Saltz, J., Gurcan, M.N.: Texture classification using nonlinear color quantization: Application to histopathological image analysis. In: IEEE ICASSP 2008, Las Vegas, NV, March 30-April 4 (2008)
Belkacem-Boussaid, K., Sertel, O., Lozanski, G., Shana’aah, A., Gurcan, M.N.: Extraction of color features in the spectral domain to recognize centroblasts in histopathology. In: IEEE EMBC 2009, Minneapolis, MN, September 2-6 (2009)
Samsi, S., Krishnamurthy, A.K., Groseclose, M., Caprioli, R.M., Lozanski, G., Gurcan, M.N.: Imaging Mass Spectrometry Analysis for Follicular Lymphoma Grading. In: IEEE EMBC 2009, Minneapolis, MN, September 2-6 (2009)
Teodoro, G., Sachetto, R., Sertel, O., Gurcan, M.N., Meira, W., Catalyurek, U., Ferreira, R.: Coordinating the use of GPU and CPU for improving performance of compute intensive applications. In: IEEE Cluster 2009, New Orleans, LA, August 31 – September 4 (2009)
Belkacem-Boussaid, K., Prescott, J., Lozanski, G., Gurcan, M.N.: Segmentation of follicular regions on H&E slides using matching filter and active contour models. In: SPIE Medical Imaging 2010, San Diego, California, February 13-18 (2010)
Belkacem-Boussaid, K., Pennell, M., Lozanski, G., Shana’ah, A., Gurcan, M.N.: Effect of pathologist agreement on evaluating a computer-assisted system: Recognizing centroblasts in follicular lymphoma cases. In: IEEE ISBI 2010, Rotterdam, The Netherlands, April 14-17 (2010)
Cheng, J., Veronika, M., Rajapakse, J.: Identifying Cells in Histopathological Images. In: Ünay, D., Çataltepe, Z., Aksoy, S. (eds.) ICPR 2010. LNCS, vol. 6388, pp. 247–255. Springer, Heidelberg (2010)
Gupta, S., Kuse, M., Sharma, T.: A Classification Scheme for Lymphocyte Segmentation in H&E Stained Histology Images. In: Ünay, D., Çataltepe, Z., Aksoy, S. (eds.) ICPR 2010. LNCS, vol. 6388, pp. 237–245. Springer, Heidelberg (2010)
Panagiotakis, C., Ramasso, E., Tziritas, G.: Lymphocyte Segmentation using the Transferable Belief Model. In: Ünay, D., Çataltepe, Z., Aksoy, S. (eds.) ICPR 2010. LNCS, vol. 6388, pp. 256–265. Springer, Heidelberg (2010)
Graf, F., Grzegorzek, M., Paulus, D.: Counting Lymphocytes in Histopathology Images Using Connected Components. In: Ünay, D., Çataltepe, Z., Aksoy, S. (eds.) ICPR 2010. LNCS, vol. 6388, pp. 267–273. Springer, Heidelberg (2010)
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Gurcan, M.N., Madabhushi, A., Rajpoot, N. (2010). Pattern Recognition in Histopathological Images: An ICPR 2010 Contest. In: Ünay, D., Çataltepe, Z., Aksoy, S. (eds) Recognizing Patterns in Signals, Speech, Images and Videos. ICPR 2010. Lecture Notes in Computer Science, vol 6388. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17711-8_23
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DOI: https://doi.org/10.1007/978-3-642-17711-8_23
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