Advanced biomedical imaging for plaque lesion diagnosis focusing on Malaysian subjects / Hadzli Hashim

This thesis describes the development of a novel non-invasive color based intelligent diagnosis model for plaque psoriasis lesion focusing on Malaysian subjects. The system which is based on primary color components from digital images employed new algorithms of data acquisition, data processing, da...

Full description

Saved in:

Bibliographic Details
Main Author:	Hashim, Hadzli
Format:	Thesis
Language:	English
Published:	2006
Subjects:	Biomedical engineering
Online Access:	https://ir.uitm.edu.my/id/eprint/101740/1/101740.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uitm-ir.101740
record_format	uketd_dc
spelling	my-uitm-ir.1017402024-12-10T02:21:13Z Advanced biomedical imaging for plaque lesion diagnosis focusing on Malaysian subjects / Hadzli Hashim 2006 Hashim, Hadzli Biomedical engineering This thesis describes the development of a novel non-invasive color based intelligent diagnosis model for plaque psoriasis lesion focusing on Malaysian subjects. The system which is based on primary color components from digital images employed new algorithms of data acquisition, data processing, data extraction and application of artificial neural network (ANN) as the decision model to discriminate plaque from other major psoriasis. Two major works were carried out; one was the extraction process of a single color component for plaque discrimination through application of known statistical tools on the clustering pixel gradation indices of each color component in terms of location and shape. Second part of the work was to design the ANN diagnosis models by utilizing the extracted single color spectrum with various combinations of its gradation indices. A multi color spectrum ANN model, where it used all the three primary components was designed and treated as a controlled system. These models were evaluated and validated through analysis of the performance indicators applied in medical research; sensitivity, specificity, clustering properties and discriminative power of the models by plotting the effects of threshold adjustment on their diagnostic accuracy, error and uncertainty (DA, DE and DU), and the optimum Euclidean Distance (ED) from the ideal point (1,0) in the receiver operating characteristics (ROC) plot. Other than that, the respective model’s network structure was also considered. 2006 Thesis https://ir.uitm.edu.my/id/eprint/101740/ https://ir.uitm.edu.my/id/eprint/101740/1/101740.pdf text en public phd doctoral Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Biomedical engineering
spellingShingle	Biomedical engineering Hashim, Hadzli Advanced biomedical imaging for plaque lesion diagnosis focusing on Malaysian subjects / Hadzli Hashim
description	This thesis describes the development of a novel non-invasive color based intelligent diagnosis model for plaque psoriasis lesion focusing on Malaysian subjects. The system which is based on primary color components from digital images employed new algorithms of data acquisition, data processing, data extraction and application of artificial neural network (ANN) as the decision model to discriminate plaque from other major psoriasis. Two major works were carried out; one was the extraction process of a single color component for plaque discrimination through application of known statistical tools on the clustering pixel gradation indices of each color component in terms of location and shape. Second part of the work was to design the ANN diagnosis models by utilizing the extracted single color spectrum with various combinations of its gradation indices. A multi color spectrum ANN model, where it used all the three primary components was designed and treated as a controlled system. These models were evaluated and validated through analysis of the performance indicators applied in medical research; sensitivity, specificity, clustering properties and discriminative power of the models by plotting the effects of threshold adjustment on their diagnostic accuracy, error and uncertainty (DA, DE and DU), and the optimum Euclidean Distance (ED) from the ideal point (1,0) in the receiver operating characteristics (ROC) plot. Other than that, the respective model’s network structure was also considered.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Hashim, Hadzli
author_facet	Hashim, Hadzli
author_sort	Hashim, Hadzli
title	Advanced biomedical imaging for plaque lesion diagnosis focusing on Malaysian subjects / Hadzli Hashim
title_short	Advanced biomedical imaging for plaque lesion diagnosis focusing on Malaysian subjects / Hadzli Hashim
title_full	Advanced biomedical imaging for plaque lesion diagnosis focusing on Malaysian subjects / Hadzli Hashim
title_fullStr	Advanced biomedical imaging for plaque lesion diagnosis focusing on Malaysian subjects / Hadzli Hashim
title_full_unstemmed	Advanced biomedical imaging for plaque lesion diagnosis focusing on Malaysian subjects / Hadzli Hashim
title_sort	advanced biomedical imaging for plaque lesion diagnosis focusing on malaysian subjects / hadzli hashim
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Electrical Engineering
publishDate	2006
url	https://ir.uitm.edu.my/id/eprint/101740/1/101740.pdf
_version_	1818588012030722048

Advanced biomedical imaging for plaque lesion diagnosis focusing on Malaysian subjects / Hadzli Hashim

Similar Items