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dc.contributor.advisorChakrabarty, Dr. Amitabha
dc.contributor.authorKamal, Nahid
dc.contributor.authorIslam, Subrina
dc.contributor.authorAsad, Al Faysal Bin
dc.contributor.authorKhatun, Sumaiya
dc.date.accessioned2018-01-11T05:56:20Z
dc.date.available2018-01-11T05:56:20Z
dc.date.copyright2017
dc.date.issued2017
dc.identifier.otherID 12201058
dc.identifier.otherID 13301139
dc.identifier.otherID-13101095
dc.identifier.otherID-12201099
dc.identifier.urihttp://hdl.handle.net/10361/9021
dc.descriptionThis thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.en_US
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (pages 41-42).
dc.description.abstractTuberculosis is most common contagious disease. Nowadays, millions of human beings of the world are suffering from it. We will use the most used worldwide method Ziehl-Neelsen stain (ZN-stain) to detect Tuberculosis which is based on sputum examination microscopically. This method needs expert human resources and implicit examination. The main constraints are expertise human,time and cost to implement our process. We will use Thresholding, multi-stage, color-based Bayesian segmentation identified possible ‘Tuberculosis objects’, removed artifacts by shape comparison and color-labeled objects as ‘definite’, ‘possible’ or ‘non-Tuberculosis’, bypassing photomicrographic calibration.In our work, we will use an algorithm based on image processing is developed for identification of Tuberculosis.en_US
dc.description.statementofresponsibilityNahid Kamal
dc.description.statementofresponsibilitySubrina Islam
dc.description.statementofresponsibilityAl Faysal Bin Asad
dc.description.statementofresponsibilitySumaiya Khatun
dc.format.extent42 pages
dc.language.isoenen_US
dc.publisherBARC Universityen_US
dc.rightsBRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectTuberculosisen_US
dc.subjectInfectious diseaseen_US
dc.subjectImage processingen_US
dc.subjectAlgorithmen_US
dc.subjectZiehl-Neelsen stainen_US
dc.titleTuberculosis diagnosis through image processingen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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