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Inventi Impact: Image & Video Processing

Articles

  • Inventi:eiv/42555/21
    Comparison of Multispectral Image-Processing Methods for Brain Tissue Classification in BrainWeb Synthetic Data and Real MR Images
    01-Jul-2021 Research 2021 : July - September
    Hsian-Min Chen, Hung-Chieh Chen, Clayton Chi-Chang Chen, Yung-Chieh Chang, Yi-Ying Wu, Wen-Hsien Chen, Chiu-Chin Sung, Jyh-Wen Chai, San-Kan Lee

    Accurate quantification of brain tissue is a fundamental and challenging task in neuroimaging. Over the past two decades, statistical parametric mapping (SPM) and FMRIB’s Automated Segmentation Tool (FAST) have been widely used to estimate gray matter (GM) and white matter (WM) volumes. However, they cannot reliably estimate cerebrospinal fluid (CSF) volumes. To address this problem, we developed the TRIO algorithm (TRIOA), a new magnetic resonance (MR) multispectral classification method. SPM8, SPM12, FAST, and the TRIOA were evaluated using the BrainWeb database and real magnetic resonance imaging (MRI) data. In this paper, the MR brain images of 140 healthy volunteers (51:5 ± 15:8 y/o) were obtained using a whole-body 1.5 T MRI system (Aera, Siemens, Erlangen, Germany)..........

    How to Cite this Article
    Attribution/ CC Compliant Citation: Chen, Hsian-Min, et al. "Comparison of Multispectral Image-Processing Methods for Brain Tissue Classification in BrainWeb Synthetic Data and Real MR Images." BioMed Research International 2021 (2021). https://doi.org/10.1155/2021/9820145 http://creativecommons.org/licenses/by/4.0/ Some formatting elements, header, footer, logos, dates and pagination were modified while adapting this article.
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