Computers in Biology and Medicine, ( ISI ), Volume (41), No (7), Year (2011-7) , Pages (427-434)

Title : ( Automatic evaluation of pressure sore status by combining information obtained from high-frequency ultrasound and digital photography )

Authors: Sahar Moghimi , Mohhamad Hossein Miran Baygi , Giti Torkaman ,

Citation: BibTeX | EndNote

Abstract

In this study, the different phases of pressure sore generation and healing are investigated through a combined analysis of high-frequency ultrasound (20 MHz) images and digital color photographs. Pressure sores were artificially induced in guinea pigs, and the injured regions were monitored for 21 days (data were obtained on days 3, 7, 14, and 21). Several statistical features of the images were extracted, relating to both the altering pattern of tissue and its superficial appearance. The features were grouped into five independent categories, and each category was used to train a neural network whose outputs were the four days. The outputs of the five classifiers were then fused using a fuzzy integral to provide the final decision. We demonstrate that the suggested method provides a better decision regarding tissue status than using either imaging technique separately. This new approach may be a viable tool for detecting the phases of pressure sore generation and healing in clinical settings.

Keywords

Digital color images; Sonographic assessment; Color histogram; Feature extraction; Image processing; Fuzzy integral; Neural networks; Pressure sore; Guinea pigs
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@article{paperid:1024170,
author = {Moghimi, Sahar and Mohhamad Hossein Miran Baygi and Giti Torkaman},
title = {Automatic evaluation of pressure sore status by combining information obtained from high-frequency ultrasound and digital photography},
journal = {Computers in Biology and Medicine},
year = {2011},
volume = {41},
number = {7},
month = {July},
issn = {0010-4825},
pages = {427--434},
numpages = {7},
keywords = {Digital color images; Sonographic assessment; Color histogram; Feature extraction; Image processing; Fuzzy integral; Neural networks; Pressure sore; Guinea pigs},
}

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%0 Journal Article
%T Automatic evaluation of pressure sore status by combining information obtained from high-frequency ultrasound and digital photography
%A Moghimi, Sahar
%A Mohhamad Hossein Miran Baygi
%A Giti Torkaman
%J Computers in Biology and Medicine
%@ 0010-4825
%D 2011

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