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Automated Detection of Lung Tuberculosis Based on X-ray Image Analysis

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dc.contributor.author Oo, May Thitsa
dc.contributor.author Htway, Thin Thin
dc.date.accessioned 2019-07-24T15:16:05Z
dc.date.available 2019-07-24T15:16:05Z
dc.date.issued 2010-12-16
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1245
dc.description.abstract Detection of lung tuberculosis is mostly based on X-ray images. Image segmentation is important in different fields of image processing. Image segmentation is process of dividing images according to its characteristics. Different methods are presented for image segmentation. In this paper to find nodules, symptoms of diseases in X-ray images, we use watershed segmentation approach. First take the gray scale image and then applying the watershed segmentation approach to segment the image with catchment basins. When the lung image is isolated from X-ray image, the suspected nodule pixels in the lung can be found. Based on nodules and user’s input symptoms, patient can be defined either suffer from lung TB or not. en_US
dc.language.iso en en_US
dc.publisher Fifth Local Conference on Parallel and Soft Computing en_US
dc.subject watershed transformation en_US
dc.subject catchment basins en_US
dc.subject lung tuberculosis en_US
dc.title Automated Detection of Lung Tuberculosis Based on X-ray Image Analysis en_US
dc.type Article en_US

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