NDLI: Differentiation of EMCI in sMR images using segmented brainstem multifractal texture measures

Content Provider	IET Digital Library
Author	Palanisamy, R. Swaminathan, R. Sundar, S.
Abstract	In this Letter, an attempt has been made to segment the brainstem structure from structural magnetic resonance (sMR) images and differentiate early mild cognitive impairment (EMCI) from normal and Alzheimer's condition using multifractal texture measures. The images considered from public domain database are preprocessed and brainstem is segmented using fuzzy ‘C’ means-based connected component labelling method. Multifractal spectrum (MS) is evaluated for the segmented brainstem structure using the multifractal detrended moving average technique. Seven MS-based texture measures are extracted and statistically analysed using one-way analysis of variance. Classification algorithms namely, naïve Bayes, decision tree and random forest (RF) are employed to distinguish the EMCI condition. Ten-fold cross-validation approach is executed and its performance is evaluated using accuracy, precision, recall and area under the curve. The results indicate that the segmented brainstem structures possess multifractal characteristics. Of the extracted MS-based texture measures, α max, α 0, αR, B and Δα are found to be statistically significant. RF gives the highest accuracy of 92.3% in distinguishing EMCI from other subject groups. Hence, the proposed approach with brainstem MS-based texture measures in combination with RF can be used as an imaging biomarker for the diagnosis of EMCI.
Starting Page	1213
Ending Page	1214
Page Count	2
ISSN	00135194
Volume Number	55
e-ISSN	1350911X
Issue Number	Issue 23, Nov (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/55/23
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2019.2821
Journal	Electronics Letters
Publisher Date	2019-09-30
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Alzheimer's Condition Bayes Method Biology And Medical Computing Biomarker Imaging Biomedical Magnetic Resonance Imaging Biomedical MRI Biophysics of Neurophysiological Processes Brain Brainstem Multifractal Spectrum-based Texture Measures Cognition Component Labelling Method Computer Vision And Image Processing Technique Decision Tree Diseases Early Mild Cognitive Impairment Extracted Multifractal Spectrum-based Texture Measures Feature Extraction Fractals Fuzzy C Means-based Connected Component Labelling Method Image Classification Image Recognition Image Segmentation Image Texture Medical Image Processing Medical Magnetic Resonance Imaging And Spectroscopy Naive Bayes Neurophysiology Patient Diagnostic Method And Instrumentation Probability Theory Public Domain Database Random Forest Segmented Brainstem Multifractal Texture Measures Spectroscopy Statistical Analysis Statistics Stochastic Linearised SCUC Structural Magnetic Resonance Image
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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