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Fractal analysis and fuzzy c-means clustering for quantification of fibrotic microscopy images

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Abstract

The advances in improved fluorescent probes and better cameras in collaboration with the advent of computers in imaging and image analysis, assist the task of diagnosis in microscopy imaging. Based on such technologies, we introduce a computer-assisted image characterization tool based on fractal analysis and fuzzy clustering for the quantification of degree of the Idiopathic Pulmonary Fibrosis in microscopy images. The implementation of this algorithmic strategy proved very promising concerning the issue of the automated assessment of microscopy images of lung fibrotic regions against conventional classification methods that require training such as neural networks. Fractal dimension is an important image feature that can be associated with pathological fibrotic structures as is shown by our experimental results.

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Acknowledgments

The authors would like to thank the European Union (European Social Fund ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)—Research Funding Program: “Heracleitus II. Investing in knowledge society through the European Social Fund.” for financially supporting this work. Part of this work has been also funded by Program: Thalis—Interdisciplinary Research in Affective Computing for Biological Activity Recognition in Assistive Environments/Operational Program “Education and Lifelong Learning”.

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Authors and Affiliations

  1. Department of Computer Science and Biomedical Informatics, University of Central Greece, Papassiopoulou 2–4, 35100 , Lamia, Greece

    S. K. Tasoulis & V. P. Plagianakos

  2. Department of Digital Systems, University of Piraeus, Grigoriou Lampraki 126, 18532 , Piraeus, Greece

    I. Maglogiannis

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  1. S. K. Tasoulis
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  2. I. Maglogiannis
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  3. V. P. Plagianakos
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Correspondence to I. Maglogiannis.

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Tasoulis, S.K., Maglogiannis, I. & Plagianakos, V.P. Fractal analysis and fuzzy c-means clustering for quantification of fibrotic microscopy images. Artif Intell Rev 42, 313–329 (2014). https://doi.org/10.1007/s10462-013-9408-9

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