SECONDARY PULMONARY TUBERCULOSIS RECOGNITION BY ROTATION ANGLE VECTOR GRID-BASED FRACTIONAL FOURIER ENTROPY
Copyright policy )SECONDARY PULMONARY TUBERCULOSIS RECOGNITION BY ROTATION ANGLE VECTOR GRID-BASED FRACTIONAL FOURIER ENTROPY
Aim: Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis bacteria. This study plans to build a novel deep learning-based model for the accurate recognition of tuberculosis. Methods: We propose a novel model — rotation angle vector grid-based fractional Fourier entropy and deep stacked sparse autoencoder (RAVG-FrFE–DSSAE) — which uses RAVG-FrFE as a feature extractor and harnesses DSSAE as the classifier. Moreover, an 18-way MDA is introduced on the training set to avoid overfitting. Results: Experimental results of 10 runs of 10-fold CV showcase that this proposed RAVG-FrFE–DSSAE algorithm yields a reasonable performance including of 93.68[Formula: see text]±[Formula: see text]1.11% sensitivity, 94.38[Formula: see text]±[Formula: see text]1.11% specificity, 94.35[Formula: see text]±[Formula: see text]1.04% precision, 94.03[Formula: see text]±[Formula: see text]0.69% accuracy, 94.01[Formula: see text]±[Formula: see text]0.70% [Formula: see text]-score, 88.07[Formula: see text]±[Formula: see text]1.38% MCC, 94.01[Formula: see text]±[Formula: see text]0.70% FMI, and 0.9725 AUC, respectively. Conclusions: Our result outperforms the eight state-of-the-art approaches. Besides, the result shows the effectiveness of the 18-way MDA.
- University of Massachusetts Medical School United States
- University of Leicester United Kingdom
Biomedical imaging and signal processing, fractional Fourier entropy, deep learning, fractional Fourier transform, multiple-way data augmentation, Fourier and Fourier-Stieltjes transforms and other transforms of Fourier type, Fractional derivatives and integrals, rotation angle vector grid, secondary pulmonary tuberculosis, recognition, deep stacked sparse autoencoder
Biomedical imaging and signal processing, fractional Fourier entropy, deep learning, fractional Fourier transform, multiple-way data augmentation, Fourier and Fourier-Stieltjes transforms and other transforms of Fourier type, Fractional derivatives and integrals, rotation angle vector grid, secondary pulmonary tuberculosis, recognition, deep stacked sparse autoencoder
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