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Texture anisotropy technique in brain degenerative diseases

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Abstract

Structural alterations anisotropy-based measured for different areas for the most common types of dementia diseases could be a biomarker of brain impairment. The current work aims to assess whether texture anisotropy can discriminate both healthy versus Alzheimer’s and Pick’s patients based on regional evaluation while maintaining high predictive power. The investigated area is reduced from the whole-brain surface to three major lobes (i.e., frontal, temporal and parietal). A predictive model was proposed to associate a disease with a specific area in the brain based on the anisotropy values. Simultaneous analysis of 1680 measurements from 105 brain magnetic resonance images acquired as T2w and PD sequences was performed to establish the significance of the model. The cerebral calcinosis disease has been used as artificial ground truth. The association based on textural anisotropy between targeted diseases and control patients was performed by using Pearson’s correlation coefficients. A new proposed consistency index investigated the texture anisotropy relevance for all image’s types and all analyzed classes and regions. The validation study is based on area under the receiver-operating characteristic curve that depicted the overall diagnostic performance of the texture anisotropy in each region. The proposed model demonstrated that texture anisotropy is accurate solution in diagnosis of Alzheimer’s and Pick’s diseases when the investigated area is reduced to major lobes, with sensitivity >90% and specificity >80%.

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Acknowledgements

The second author (S.M.) would like to thank Project PERFORM ID POSDRU/159/1.5/S/138963 of ‘Dunărea de Jos’ University of Galati, Romania for the support.

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Authors and Affiliations

  1. Department of Chemistry, Physics and Environment, Faculty of Sciences and Environment, Dunarea de Jos University of Galaţi, 47 Domneasca St., 800008, Galaţi, Romania

    Luminiţa Moraru, Simona Moldovanu & Lucian Traian Dimitrievici

  2. Dumitru Motoc High School, 15 Milcov St., 800509, Galaţi, Romania

    Simona Moldovanu

  3. Department of Computer Science and Engineering, Electrical and Electronics Engineering, Faculty of Control Systems, Computers, Dunarea de Jos University of Galaţi, Galaţi, Romania

    Simona Moldovanu

  4. Mihail Kogalniceanu High School, 131B Brailei ST, 800379, Galaţi, Romania

    Lucian Traian Dimitrievici

  5. Department of Electronics and Electrical Communications Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt

    Amira S. Ashour

  6. Department of Information Technology, Techno India College of Technology, Kolkata, India

    Nilanjan Dey

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  1. Luminiţa Moraru
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  2. Simona Moldovanu
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Correspondence to Amira S. Ashour.

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Moraru, L., Moldovanu, S., Dimitrievici, L.T. et al. Texture anisotropy technique in brain degenerative diseases. Neural Comput & Applic 30, 1667–1677 (2018). https://doi.org/10.1007/s00521-016-2777-7

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