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Differentiation of early mild cognitive impairment in brainstem MR images using multifractal detrended moving average singularity spectral features
Published in Elsevier Ltd
2020
Volume: 57
   
Abstract
Brainstem texture analysis can provide valuable information in the diagnosis of Early Mild Cognitive Impairment (EMCI) condition. In this work, 3D brainstem structure is segmented and analysed for texture alterations using multifractal features to differentiate EMCI from other Alzheimer's disease stages. The images obtained from public domain database are preprocessed for spatial registration, skull stripping and contrast enhancement. White matter volume is segmented from the preprocessed images using fuzzy ‘C’ means clustering algorithm. Midsagittal white matter tissue is used as the initial seed to segment the brainstem volume using sparse field level set method. Multifractal detrended moving average algorithm is used to compute the fluctuation function, generalized Hurst exponent and mass exponent to study the multifractal characteristics of brainstem structure. Features extracted from the multifractal spectrum are analysed to differentiate the images pertaining to EMCI subject group. Results indicate that the proposed technique is able to segment the brainstem structure from all the considered images. The fluctuation function is observed to have linear relationship with scale. The generalized Hurst exponent decreases with order and mass exponent follows a non-linear trend demonstrating the multifractal nature of brainstem. Singularity spectral features namely strength of multifractality, Holder exponent at f(2.8), tangent slope and maximum Holder exponent are found to be most significant in differentiating EMCI from subject groups. As this complex EMCI distinction is clinically important, the proposed approach is useful for early diagnosis of Alzheimer's condition. © 2019 Elsevier Ltd
About the journal
JournalData powered by TypesetBiomedical Signal Processing and Control
PublisherData powered by TypesetElsevier Ltd
ISSN17468094
Open AccessNo
Concepts (50)
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    Brain
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    Clustering algorithms
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    Diagnosis
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    Fractals
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    Image segmentation
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    Magnetic resonance imaging
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    Neurodegenerative diseases
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    Numerical methods
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    Signal theory
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    Textures
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    Alzheimer's disease
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    BRAINSTEM
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    DETRENDING MOVING AVERAGES
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    MEANS CLUSTERING
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    MILD COGNITIVE IMPAIRMENTS
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    Spectral feature
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    Image enhancement
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    Alzheimer disease
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    Article
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    Brain size
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    BRAIN STEM
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    Contrast enhancement
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    Controlled study
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    Differential diagnosis
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    Early diagnosis
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    EARLY MILD COGNITIVE IMPAIRMENT
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    Feature extraction
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    Fractal analysis
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    Fuzzy c means clustering
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    GENERALIZED HURST EXPONENT
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    Holder exponent
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    Human
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    Image processing
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    Image registration
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    IMAGE REGISTRATION ALGORITHM
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    IMAGING ALGORITHM
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    LATE MILD COGNITIVE IMPAIRMENT
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    MASS EXPONENT
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    Mathematical parameters
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    Mild cognitive impairment
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    MULTIFRACTAL DETRENDED MOVING AVERAGE ALGORITHM
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    Neuroimaging
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    Nonlinear system
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    Nuclear magnetic resonance imaging
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    Priority journal
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    SKULL STRIPPING FILTER
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    STAGING
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    TANGENT SLOPE
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    Three dimensional imaging
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    WHITE MATTER