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Bidimensional Fuzzy Entropy: Principle Analysis and Biomedical Applications.
Summary
A new bidimensional fuzzy entropy (FuzEn2D) measure offers superior image analysis, showing low parameter sensitivity and invariance to rotation and translation. This advanced entropy method shows promise for biomedical applications, including skin lesion diagnostics.
Area of Science:
- Image Processing
- Biomedical Imaging
- Entropy Measures
Background:
- Entropy measures have evolved from 1D to 2D for image analysis.
- Existing 2D entropy measures have limitations in assessing image irregularity.
Purpose of the Study:
- Introduce and evaluate a novel 2D entropy measure: bidimensional fuzzy entropy (FuzEn2D).
- Assess FuzEn2D's performance, parameter sensitivity, and invariance properties.
- Demonstrate FuzEn2D's multiscale application in biomedical image analysis.
Main Methods:
- Developed and applied the bidimensional fuzzy entropy (FuzEn2D) measure.
- Validated FuzEn2D using synthetic images with controlled noise and randomness.
- Tested FuzEn2D on texture datasets and real-world biomedical images (dermoscopic).
Main Results:
- FuzEn2D demonstrated low sensitivity to parameter selection.
- The measure proved to be invariant to image rotation and translation.
- FuzEn2D outperformed existing 2D entropy measures in synthetic image analysis.
- Multiscale FuzEn2D showed potential in differentiating between melanoma and melanocytic nevi.
Conclusions:
- Bidimensional fuzzy entropy (FuzEn2D) is a robust and effective measure for image irregularity.
- FuzEn2D's invariance and performance suggest its utility in various image processing tasks.
- The multiscale extension of FuzEn2D holds promise for computer-aided diagnosis in dermatology.
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