Coronary Plaque Boundary Enhancement in IVUS Image by Using a Modified Perona-Malik Diffusion Filter

Area of Science:

• Medical Imaging
• Image Processing
• Cardiology

Background:

• Intravascular ultrasound (IVUS) images are crucial for diagnosing acute coronary syndrome (ACS).
• IVUS images suffer from significant speckle noise, degrading image quality.
• Standard Perona-Malik diffusion (PMD) filters can obscure coronary plaque boundaries when reducing noise.

Purpose of the Study:

• To develop a modified Perona-Malik diffusion (PMD) filter tailored for intravascular ultrasound (IVUS) imaging.
• To improve the enhancement of coronary plaque boundaries in noisy IVUS images.
• To achieve accurate plaque boundary detection for better ACS diagnosis.

Main Methods:

• A modified Perona-Malik diffusion (PMD) filter was designed specifically for coronary plaque boundary enhancement in IVUS images.
• The modified PMD filter was applied to reduce speckle noise while preserving and enhancing plaque edges.
• Subsequent application of the Takagi-Sugeno fuzzy model was used for coronary plaque boundary detection.

Main Results:

• The modified PMD filter effectively reduced speckle noise in IVUS images.
• Coronary plaque boundaries were clearly enhanced and preserved.
• The combined method demonstrated successful and accurate detection of coronary plaque boundaries.

Conclusions:

• The proposed modified PMD filter offers a significant improvement for analyzing IVUS images.
• This technique enhances coronary plaque boundary detection, aiding in the diagnosis of ACS.
• Numerical experiments confirmed the accuracy and effectiveness of the proposed method.