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Segmentation of MRI brain scans using spatial constraints and 3D features.

This paper presents a novel unsupervised algorithm for brain tissue segmentation in magnetic resonance imaging (MRI). The proposed algorithm, named Gardens2, adopts a clustering approach to segment voxels of a given MRI into three classes: cerebrospinal fluid (CSF), gray matter (GM), and white matte...

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Published in:Medical & Biological Engineering & Computing Vol. 58; no. 12; pp. 3101 - 3113
Main Authors: Grande-Barreto, Jonas, Gómez-Gil, Pilar
Format: Journal Article
Published: Springer Nature 2020
Online Access:View this record in EBSCOhost
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      dt: 2020
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s11517-020-02270-1
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        atl: Segmentation of MRI brain scans using spatial constraints and 3D features.
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        au:
          Grande-Barreto, Jonas
          Gómez-Gil, Pilar
        affil: National Institute for Astrophysics, Optics and Electronics (INAOE), Puebla, Mexico
      sug:
        subj:
          Brain
          Magnetic Resonance Imaging
          Neuroradiography
          Image Processing, Computer Assisted
          Gray Matter
          Algorithms
      ab: This paper presents a novel unsupervised algorithm for brain tissue segmentation in magnetic resonance imaging (MRI). The proposed algorithm, named Gardens2, adopts a clustering approach to segment voxels of a given MRI into three classes: cerebrospinal fluid (CSF), gray matter (GM), and white matter (WM). Using an overlapping criterion, 3D feature descriptors and prior atlas information, Gardens2 generates a segmentation mask per class in order to parcellate the brain tissues. We assessed our method using three neuroimaging datasets: BrainWeb, IBSR18, and IBSR20, the last two provided by the Internet Brain Segmentation Repository. Its performance was compared with eleven well established as well as newly proposed unsupervised segmentation methods. Overall, Gardens2 obtained better segmentation performance than the rest of the methods in two of the three databases and competitive results when its performance was measured by class. Graphical Abstract Brain tissue segmentation using 3D features and an adjusted atlas template.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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