1. bookVolume 75 (2020): Issue 1 (April 2020)
    Applied Mathematics'19
Journal Details
License
Format
Journal
eISSN
1338-9750
First Published
12 Nov 2012
Publication timeframe
3 times per year
Languages
English
access type Open Access

Macrophage Image Segmentation by Thresholding and Subjective Surface Method

Published Online: 24 Apr 2020
Page range: 103 - 120
Received: 04 Jul 2019
Journal Details
License
Format
Journal
eISSN
1338-9750
First Published
12 Nov 2012
Publication timeframe
3 times per year
Languages
English
Abstract

We introduce two level-set method approaches to segmentation of 2D macrophage images. The first one is based on the Otsu thresholding and the second one on the information entropy thresholding, both followed by the classical subjective surface (SUBSURF) method. Results of both methods are compared with the semi-automatic Lagrangian method in which the segmentation curve evolves along the edge of the macrophage and it is controlled by an expert user. We present the comparison of all three methods with respect to the Hausdorff distance of resulting segmentation curves and we compare also their perimeter and enclosed area. We show that accuracy of the automatic SUBSURF method is comparable to the results of the semi-automatic Lagrangian segmentation.

Keywords

MSC 2010

[1] AHUJA, N.—ROSENFELD, A.: A Note on the Use of Second-Order Gray Level Statistics for Threshold Selection, IEEE Transactions on Systems, Man, and Cybernetics 8(12) (1978), 895-898.10.1109/TSMC.1978.4309892Search in Google Scholar

[2] ALT, H.—BEHRENDS, B.—BLÖMER, J.: Approximate matching of polygonal shapes, Annals of Mathematics and Artificial Intelligence 13(3-4) (1995), 251–265.10.1007/BF01530830Search in Google Scholar

[3] CHANG, C. I.—CHEN, K.—WANG, J.—ALTHOUSE, M. L.: A relative entropy-based approach to image thresholding, Pattern Recognition 27(9) (1994), 1275–1289.10.1016/0031-3203(94)90011-6Search in Google Scholar

[4] CHANWIMALUANG, T.—FAN, G.: An efficient blood vessel detection algorithm for retinal images using local entropy thresholding.In:Proceedings of the 2003 International Symposium on Circuits and Systems, May, 2003. IEEE Vol. 5, 2003, pp. 21–24.Search in Google Scholar

[5] HUTTENLOCHER, D. P.—KLANDERMAN, G. A.—RUCKLIDGE, W. A.: Comparing Images Using the Hausdorff Distance, IEEE Transactions on Pattern Analysis and Machine Intelligence 15(9) (1993), 850–863.10.1109/34.232073Search in Google Scholar

[6] LEWIS, C. E.—POLLARD, J. W.: Distinct role of macrophages in different tumor micro-environments, Cancer Research 66 (2006), no. 2, 605–612.Search in Google Scholar

[7] MANTOVANI, A.—SOZZANI, S.—LOCATI, M.—ALLAVENA, P.—SICA, A.: Macrophage polarization: tumor-associated macrophages as a paradigm for polarized M2 mononuclear phagocytes, Trends in Immunology 23 (2002), no. 11, 549–555.Search in Google Scholar

[8] MIKULA, K.—PEYRIÉRAS, N.—REMEŠIKOVÁ, M.—SARTI, A.: 3 D embryogenesis image segmentation by the generalized subjective surface method using the finite volume technique, Finite Volumes for Complex Applications V: Problems and Perspectives (2008), 585–592.Search in Google Scholar

[9] MIKULA, K.—URBÁN, J.—KOLLAR, M.—AMBROZ, M.—JAROLIMEK, I.—SIBIK J.—SIBIKOVA, M.: Semi-automatic segmentation of NATURA 2000 habitats in Sentinel-2 satellite images by evolving open curves, Discrete and Continuous Dynamical Systems-series S, (submitted).Search in Google Scholar

[10] OTSU, N.: A threshold selection method from gray-level histograms, IEEE transactions on systems, man, and cybernetics 9 (1979), no. 1, 62–66.Search in Google Scholar

[11] SARTI, A.—MALLADI, R.—SETHIAN, J. A.: Subjective surfaces: A method for completing missing boundaries, Proceedings of the National Academy of Sciences 97 (2000), no. 12, 6258–6263.Search in Google Scholar

[12] WU,C.M.—CHEN,Y.C.—HSIEH,K.S.: Texture features for classification of ultrasonic liver images, IEEE Transactions on medical imaging 11 (2) (1992), 141–152.10.1109/42.141636Search in Google Scholar

[13] WYNN, T. A.—CHAWLA, A.—POLLARD, J. W.: Macrophage biology in development, homeostasis and disease,Nature 496 (2013), no. 7446, 445–455.Search in Google Scholar

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