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Article Dans Une Revue IEEE Journal of Biomedical and Health Informatics Année : 2021

Three-dimensional multiscale fuzzy entropy: Validation and application to idiopathic pulmonary fibrosis

Andreia Sofia F. Gaudêncio
Pedro Vaz
Joao Cardoso
Guillaume Mahé
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Mathieu Lederlin

Résumé

Idiopathic Pulmonary Fibrosis (IPF) is a chronic, severe, and progressive lung disease with short life expectancy. Based on information theory and entropy measurement, a three-dimensional multiscale fuzzy entropy (MFE 3D) algorithm is proposed to identify IPF patients from their computed tomography (CT) volumetric data. First, the validation of the algorithm was performed by analyzing several volumetric synthetic noises (white, blue, brown, and pink), MIX(p) processes-based volumes, and texture-based volumes. The entropy values obtained by MFE 3D were consistent with the values obtained using the one, and two-dimensional versions, validating its use in biomedical data. Hence, MFE 3D was applied to CT scans to identify the existence of IPF within two different groups, one of healthy subjects (26) and another of IPF patients (26). Statistical differences were found (p < 0.05) between the entropy values of each group in 5 scale factors out of 10. These results demonstrate that MFE 3D could be an interesting metric to identify IPF in CT scans.
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Dates et versions

hal-02526971 , version 1 (31-03-2020)

Identifiants

Citer

Andreia Sofia F. Gaudêncio, Pedro Vaz, Mirvana Hilal, Joao Cardoso, Guillaume Mahé, et al.. Three-dimensional multiscale fuzzy entropy: Validation and application to idiopathic pulmonary fibrosis. IEEE Journal of Biomedical and Health Informatics, 2021, 25 (1), pp.100-107. ⟨10.1109/JBHI.2020.2986210⟩. ⟨hal-02526971⟩
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