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Computer-aided diagnosis of tuberculosis in paediatric chest X-rays using local textural analysis

Includes abstract.

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Bibliographic Details
Main Author: Mouton, Andre
Other Authors: Douglas, Tania S
Format: Thesis
Language:English
Published: Department of Human Biology 2014
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access_status_str Open Access
author Mouton, Andre
author2 Douglas, Tania S
author_browse Douglas, Tania S
Mouton, Andre
author_facet Douglas, Tania S
Mouton, Andre
author_sort Mouton, Andre
collection Thesis
description Includes abstract.
format Thesis
id oai:open.uct.ac.za:11427/3271
institution University of Cape Town (South Africa)
language eng
last_indexed 2026-06-10T12:32:39.476Z
license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2014
publishDateRange 2014
publishDateSort 2014
publisher Department of Human Biology
publisherStr Department of Human Biology
record_format dspace
source_str UCTD — University of Cape Town Open Access Repository
spelling oai:open.uct.ac.za:11427/3271 Computer-aided diagnosis of tuberculosis in paediatric chest X-rays using local textural analysis Mouton, Andre Douglas, Tania S Medicine Includes abstract. Includes bibliographical references (leaves 99-103). This report presents a computerised tool to analyse the appearance of the lung fields in paediatric chest X-rays to detect the presence of tuberculosis. The computer aided diagnosis (CAD) tool consists of 4 phases: 1) lung field segmentation; 2) lung field subdivision; 3) feature extraction and 4) classification. Lung field segmentation is performed using a semi-automatic implementation of the active shape model algorithm. Two approaches to subdividing the lung fields into regions of interest are compared. The first divides each lung field into 21 overlapping regions of varying sizes, resulting in a total of 42 regions per image; this approach is called the big region approach. The second approach divides the lung fields into a large number of overlapping circular regions of interest. The circular regions have a radius of 32 pixels and are placed on an 8 x 8 pixel grid. This approach is called the circular region approach. Textural features are extracted from each of the regions using the moments of responses to a multiscale bank of Gaussian filters. Additional positional features are added to the circular regions. 2014-07-28T18:17:35Z 2014-07-28T18:17:35Z 2009 Master Thesis Masters MSc http://hdl.handle.net/11427/3271 eng application/pdf Department of Human Biology Faculty of Health Sciences University of Cape Town
spellingShingle Medicine
Mouton, Andre
Computer-aided diagnosis of tuberculosis in paediatric chest X-rays using local textural analysis
thesis_degree_str Master's
title Computer-aided diagnosis of tuberculosis in paediatric chest X-rays using local textural analysis
title_full Computer-aided diagnosis of tuberculosis in paediatric chest X-rays using local textural analysis
title_fullStr Computer-aided diagnosis of tuberculosis in paediatric chest X-rays using local textural analysis
title_full_unstemmed Computer-aided diagnosis of tuberculosis in paediatric chest X-rays using local textural analysis
title_short Computer-aided diagnosis of tuberculosis in paediatric chest X-rays using local textural analysis
title_sort computer aided diagnosis of tuberculosis in paediatric chest x rays using local textural analysis
topic Medicine
url http://hdl.handle.net/11427/3271
work_keys_str_mv AT moutonandre computeraideddiagnosisoftuberculosisinpaediatricchestxraysusinglocaltexturalanalysis