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Bendlet Transform Based Adaptive Denoising Method for Microsection Images.

Shuli Mei1, Meng Liu1, Aleksey Kudreyko2

  • 1College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China.

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|July 27, 2022
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Summary
This summary is machine-generated.

A novel adaptive denoising method using the bendlets system effectively removes Rician noise from magnetic resonance imaging (MRI) scans. This technique preserves image clarity and outperforms existing methods in noise reduction for medical imaging.

Keywords:
Rician noisesadaptive algorithmbendlet transformmagnetic resonance imaging

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Area of Science:

  • Medical Imaging
  • Image Processing
  • Computational Science

Background:

  • Magnetic Resonance Imaging (MRI) is crucial for disease diagnosis.
  • Rician distribution is the common noise model in MRI images.
  • Existing denoising methods struggle to preserve image details.

Purpose of the Study:

  • To propose an adaptive denoising method for MRI images corrupted by Rician noise.
  • To leverage the bendlets system for sparse representation of curve contours and textures.
  • To improve noise removal while maintaining image clarity.

Main Methods:

  • Utilized the bendlets system, a second-order shearlet transform, for image representation.
  • Developed an adaptive denoising approach by identifying curve contours and textures as low-frequency components.
  • Separated Rician noise, treated as high-frequency, for effective removal.

Main Results:

  • The proposed bendlets-based method successfully identified and preserved curve contours and textures.
  • Rician noise was effectively removed without blurring important image features.
  • Achieved superior Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) values compared to shearlet transform, block matching 3D, bilateral filtering, and Wiener filtering.

Conclusions:

  • The bendlets system offers a powerful tool for sparse representation of images with curve contours, like brain MRI.
  • The proposed adaptive denoising method effectively removes Rician noise from MRI images.
  • This approach demonstrates significant improvements in denoising performance over conventional techniques.