Hybrid diffusion-steered model for suppressing multiplicative noise in ultrasonograms
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Date
2017-08
Authors
Kessy, Suzan
Maiseli, Baraka
Michael, Kisangiri
Journal Title
Journal ISSN
Volume Title
Publisher
An International Journal (SIPIJ)
Abstract
Ultrasonograms refer to images generated through ultrasonography, a technique that applies ultrasound
pulses to delineate internal structures of the body. Despite being useful in medicine, ultrasonograms usually
suffer from multiplicative noises that may limit doctors to analyse and interpret them. Attempts to address the
challenge have been made from previous works, but denoising ultrasonograms while preserving semantic
features remains an open-ended problem. In this work, we have proposed a diffusion-steered model that
gives an effective interplay between total variation and Perona-Malik models. Two parameters have been
introduced into the framework to convexify our energy functional. Also, to deal with multiplicative noise, we
have incorporated a log-based prior into the framework. Empirical results show that the proposed method
generates sharper and detailed images. Even more importantly, our framework can be evolved over a longer
time without smudging critical image features.
Sustainable Development Goals
Research Article published by An International Journal (SIPIJ) Vol.8, No.4, August 2017
Keywords
ultrasound image, Perona-Malik