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Hybrid Ant Fuzzy Algorithm for MRI Images Segmentation

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Artificial Intelligence and Soft Computing (ICAISC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11509))

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Abstract

Image segmentation is the process of subdividing an image into regions that are consistent and homogeneous in some characteristics. Image segmentation is indeed a vital process in the early diagnosis of abnormalities and treatment planning. The segmentation algorithms are applied to extract the anatomical structures and anomalies from medical images. Segmentation of Magnetic Resonance Imaging (MRI) requires a lot of time when it is performed by medical specialists. The task of automation of recognition is topical in case the correct evaluation is given. The different types of segmentation algorithms are discussed in this paper. It is true that there is no universal algorithm for medical image segmentation, wherein, the choice depends upon the image modality, characteristics of region of interest and application. There is neither a single segmentation model for all medical image modalities nor all methods are efficient for a specific medical image modality. In image processing and computer vision, segmentation is still a challenging problem in many real time applications and hence more research work is required. The Hybrid Ant Fuzzy Algorithm (HAFA) for the segmentation of MRI is considered in this paper. The parameters of the HAFA are examined for different groups of MRI images. Medical images from OsiriX set and real patient pictures were used to test the algorithm. The experimental results show that the proposed algorithm has good performance and accuracy in comparison to analogues.

This work has been supported by the Ministry of Education and Science of the Russian Federation (Project part, State task 2.918.2017).

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Author information

Authors and Affiliations

  1. Southern Federal University, Nekrasovskiy Street, 44, 347928, Taganrog, Russia

    Alexander Bozhenyuk, Samer El-Khatib, Margarita Knyazeva & Sergey Rodzin

  2. Systems Research Institute Polish Academy of Sciences, Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

Authors
  1. Alexander Bozhenyuk
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  2. Samer El-Khatib
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  3. Janusz Kacprzyk
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  4. Margarita Knyazeva
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  5. Sergey Rodzin
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Corresponding author

Correspondence to Margarita Knyazeva .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Bozhenyuk, A., El-Khatib, S., Kacprzyk, J., Knyazeva, M., Rodzin, S. (2019). Hybrid Ant Fuzzy Algorithm for MRI Images Segmentation. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2019. Lecture Notes in Computer Science(), vol 11509. Springer, Cham. https://doi.org/10.1007/978-3-030-20915-5_12

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  • DOI: https://doi.org/10.1007/978-3-030-20915-5_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20914-8

  • Online ISBN: 978-3-030-20915-5

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