Abstract
Although segmentation of biomedical image data has been paid a lot of attention for many years, this crucial task still meets the problem of the correctness of the obtained results. Especially in the case of optical microscopy, the ground truth (GT), which is a very important tool for the validation of image processing algorithms, is not available.
We have developed a toolkit that generates fully 3D digital phantoms, that represent the structure of the studied biological objects. While former papers concentrated on the modelling of isolated cells (such as blood cells), this work focuses on a representative of tissue image type, namely human colon tissue. This phantom image can be submitted to the engine that simulates the image acquisition process. Such synthetic image can be further processed, e.g. deconvolved or segmented. The results can be compared with the GT derived from the digital phantom and the quality of the applied algorithm can be measured.
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References
Netten, H., Young, I.T., van Vliet, J., Tanke, H.J., Vrolijk, H., Sloos, W.C.R.: FISH and chips: automation of fluorescent dot counting in interphase cell nuclei. Cytometry 28, 1–10 (1997)
Grigoryan, A.M., Hostetter, G., Kallioniemi, O., Dougherty, E.R.: Simulation toolbox for 3D-FISH spot-counting algorithms. Real-Time Imaging 8(3), 203–212 (2002)
Manders, E.M.M., Hoebe, R., Strackee, J., Vossepoel, A.M., Aten, J.A.: Largest contour segmentation: A tool for the localization of spots in confocal images. Cytometry 23, 15–21 (1996)
Lockett, S.J., Sudar, D., Thompson, C.T., Pinkel, D., Gray, J.W.: Efficient, interactive, and three-dimensional segmentation of cell nuclei in thick tissue sections. Cytometry 31, 275–286 (1998)
Lehmussola, A., Ruusuvuori, P., Selinummi, J., Huttunen, H., Yli-Harja, O.: Computational framework for simulating fluorescence microscope images with cell populations. IEEE Trans. Med. Imaging 26(7), 1010–1016 (2007)
Svoboda, D., Kozubek, M., Stejskal, S.: Generation of digital phantoms of cell nuclei and simulation of image formation in 3d image cytometry. Cytometry, Part A 75A(6), 494–509 (2009)
Zhao, T., Murphy, R.F.: Automated learning of generative models for subcellular location: Building blocks for systems biology. Cytometry Part A 71A(12), 978–990 (2007)
Jansová, E., Koutná, I., Krontorád, P., Svoboda, Z., KÅ™ivánková, S., ŽaloudÃk, J., Kozubek, M., Kozubek, S.: Comparative transcriptome maps: a new approach to the diagnosis of colorectal carcinoma patients using cDNA microarrays. Clinical Genetics 68(3), 218–227 (2006)
Perlin, K.: An image synthesizer. In: SIGGRAPH 1985: Proceedings of the 12th Annual Conference on Computer Graphics and Interactive Techniques, pp. 287–296. ACM Press, New York (1985)
Aurenhammer, F.: Voronoi diagrams-a survey of a fundamental geometric data structure. ACM Computing Surveys 23(3), 345–405 (1991)
Nilsson, B., Heyden, A.: A fast algorithm for level set-like active contours. Pattern Recogn. Lett. 24(9-10), 1331–1337 (2003)
Tesař, L., Smutek, D., Shimizu, A., Kobatake, H.: 3D extension of Haralick texture features for medical image analysis. In: SPPR 2007: Proceedings of the Fourth Conference on IASTED International Conference, pp. 350–355. ACTA Press (2007)
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Svoboda, D., Homola, O., Stejskal, S. (2011). Generation of 3D Digital Phantoms of Colon Tissue. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21596-4_4
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DOI: https://doi.org/10.1007/978-3-642-21596-4_4
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