Monte Carlo despeckling of transrectal ultrasound images of the prostate

Authors:
Alexander Wong;Jacob Scharcanski
Affiliations:
Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada;Instituto de Informatica and Dept. de Engenharia Eletrica, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
Venue:
Digital Signal Processing
Year:
2012

Citing 4
Cited 0

Ultrasound despeckling for contrast enhancement

IEEE Transactions on Image Processing
A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise

IEEE Transactions on Pattern Analysis and Machine Intelligence
Speckle reducing anisotropic diffusion

IEEE Transactions on Image Processing
Oriented Speckle Reducing Anisotropic Diffusion

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a novel stochastic method is developed for despeckling transrectal ultrasound (TRUS) images of the prostate. By incorporating the circular probe acquisition particularities and speckle noise statistics of TRUS images of the prostate into a likelihood-weighted Monte Carlo estimation scheme, the proposed method can better remove speckle noise while preserving image structures and details that are relevant for image screening, allowing for a better delineation of the lesion contour. Our in silico and in vivo experimental results are promising, which was confirmed by a clinical evaluation of the in vivo test cases by experienced clinicians, and indicate that our method potentially can perform better than other previously proposed methods.