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Whole Tumor Area Estimation in Incremental Brain MRI Using Dilation and Erosion-Based Binary Morphing

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Bioinformatics and Biomedical Engineering (IWBBIO 2023)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 13919))

Abstract

Magnetic resonance imaging (MRI) technology is rapidly advancing and three-dimensional (3D) scanners started to play an important role on diagnosis. However, not every medical center has access to 3D magnetic resonance imaging (MRI) devices; therefore, it is safe to state that the majority of MRI scans are still two-dimensional. According to the setup values adjusted before any scan, there might be consistent gaps between the MRI slices, especially when the increment value exceeds the thickness. The gap causes miscalculation of the lesion volumes and misjudgments when the lesions are reconstructed in three-dimensional space due to excessive interpolation. Therefore, in this paper, we present the details of three types of conventional morphing methods, one dilation-based and two erosion-based, and compare them to figure out which one provides better solution for filling up the gaps in incremental brain MRI. Among three types of morphing methods, the highest average dice score coefficient (DSC) is calculated as %91.95, which is obtained by the multiplicative dilation morphing method for HG/0004 set of BraTS 2012.

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Acknowledgment

The work and the contribution were also supported by the SPEV project, University of Hradec Kralove, Faculty of Informatics and Management, Czech Republic (ID: 2102–2023), “Smart Solutions in Ubiquitous Computing Environments”. We are also grateful for the support of student Michal Dobrovolny in consultations regarding application aspects.

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Authors and Affiliations

  1. Faculty of Informatics and Management, Center for Basic and Applied Research, University of Hradec Kralove, Rokitanskeho 62, Hradec Kralove, 500 03, Czech Republic

    Orcan Alpar & Ondrej Krejcar

  2. Malaysia Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

    Ondrej Krejcar

Authors
  1. Orcan Alpar
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  2. Ondrej Krejcar
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Correspondence to Ondrej Krejcar .

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Editors and Affiliations

  1. University of Granada, Granada, Spain

    Ignacio Rojas

  2. University of Granada, Granada, Spain

    Olga Valenzuela

  3. University of Granada, Granada, Spain

    Fernando Rojas Ruiz

  4. University of Granada, Granada, Spain

    Luis Javier Herrera

  5. University of Granada, Granada, Spain

    Francisco Ortuño

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Alpar, O., Krejcar, O. (2023). Whole Tumor Area Estimation in Incremental Brain MRI Using Dilation and Erosion-Based Binary Morphing. In: Rojas, I., Valenzuela, O., Rojas Ruiz, F., Herrera, L.J., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2023. Lecture Notes in Computer Science(), vol 13919. Springer, Cham. https://doi.org/10.1007/978-3-031-34953-9_10

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  • DOI: https://doi.org/10.1007/978-3-031-34953-9_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34952-2

  • Online ISBN: 978-3-031-34953-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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