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Fractal Geometry for Early Detection and Histopathological Analysis of Oral Cancer

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Mining Intelligence and Knowledge Exploration (MIKE 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11987))

Abstract

Oral squamous cell carcinoma (OSCC) has complex molecular structure stimulated by certain chromatin architectural changes which are not easy to be detected by the naked eye. Prediction of OSCC can be done through various clinical and histological factors. As the OSCC treatment is dependent on histological grading the recent focus is to discover the morphological changes studied by computer-assisted image analysis. One of such more specific diagnostic and prognostic factor is the analysis of the fractal geometry. Fractal Dimension (FD) is the analysis and quantification of the degree of complexity of the fractal objects. FD provides a way to precisely analyse the architecture of natural objects. The purpose of this research is to estimate Minkowski fractal dimension of histopathological images for early detection of oral cancer. The proposed model is developed for analysis medical images to estimate Minkowski fractal dimension using a box-counting algorithm that allows windowing of images for more accurate calculation in the suspected areas of oral cancerous growth.

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Authors and Affiliations

  1. SOA Deemed to be University Bhubaneswar, Bhubaneswar, 751030, Odisha, India

    Santisudha Panigrahi, Juber Rahmen, Swagatika Panda & Tripti Swarnkar

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  1. Santisudha Panigrahi
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  2. Juber Rahmen
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  3. Swagatika Panda
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  4. Tripti Swarnkar
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Correspondence to Santisudha Panigrahi .

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Editors and Affiliations

  1. National Institute of Technology, Goa, India

    Purushothama B. R.

  2. National Institute of Technology, Goa, India

    Veena Thenkanidiyoor

  3. Indian Institute of Information Technology, Sri City, India

    Rajendra Prasath

  4. Indian Institute of Information Technology, Sri City, India

    Odelu Vanga

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Panigrahi, S., Rahmen, J., Panda, S., Swarnkar, T. (2020). Fractal Geometry for Early Detection and Histopathological Analysis of Oral Cancer. In: B. R., P., Thenkanidiyoor, V., Prasath, R., Vanga, O. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2019. Lecture Notes in Computer Science(), vol 11987. Springer, Cham. https://doi.org/10.1007/978-3-030-66187-8_17

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  • DOI: https://doi.org/10.1007/978-3-030-66187-8_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-66186-1

  • Online ISBN: 978-3-030-66187-8

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