Ultrasound Image Denoising via Maximum a Posteriori Estimation of Wavelet Coefficients

Abstract

Speckle noise removal by means of digital image processors could improve the diagnostic potential of medical ultrasound. This paper addresses the speckle suppression issue wit bin the framework of wave let analysis. As a first step of our approach, the logarithm of the original image is decomposed into several scales through a multiresolution analysis employing the 2-D wavelet transform. Then, we design a maximum a posteriori (MAP) estimator, which relies on a recently introduced statistical representation for the wavelet coefficients of ultrasound images. We use an alpha-stable model to develop a blind noise-removal processor that performs a non-linear operation on the data. Finally we compare our technique to current state-of-the-art denoising methods applied on actual ultrasound images and we find it more effective both in terms of speckle reduction and signal detail preservation.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA411631

Entities

People

  • A. Achim
  • A. Bezerianos
  • P. Tsakalides

Organizations

  • University of Patras

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Amplitude
  • Bayesian Networks
  • Coefficients
  • Detectors
  • Diagnostic Imaging
  • Estimators
  • Magnetic Resonance
  • Measurement
  • Models
  • Probability
  • Random Variables
  • Statistics
  • Two Dimensional
  • Ultrasounds
  • Wavelet Transforms

Fields of Study

  • Computer science

Readers

  • Image Processing and Computer Vision.
  • Medical Imaging.
  • Statistical inference.