Tuberculosis diagnosis through image processing

This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.

ग्रंथसूची विवरण
मुख्य लेखकों:	Kamal, Nahid, Islam, Subrina, Asad, Al Faysal Bin, Khatun, Sumaiya
अन्य लेखक:	Chakrabarty, Dr. Amitabha
स्वरूप:	थीसिस
भाषा:	English
प्रकाशित:	BRAC University 2017
विषय:	Tuberculosis Ziehl-Neelsen stain Bayesian segmentation Tuberculosis objects Photomicrographic calibration Image processing
ऑनलाइन पहुंच:	http://hdl.handle.net/10361/8716

id	10361-8716
record_format	dspace
spelling	10361-87162022-01-26T10:10:31Z Tuberculosis diagnosis through image processing Kamal, Nahid Islam, Subrina Asad, Al Faysal Bin Khatun, Sumaiya Chakrabarty, Dr. Amitabha Department of Computer Science and Engineering, BRAC University Tuberculosis Ziehl-Neelsen stain Bayesian segmentation Tuberculosis objects Photomicrographic calibration Image processing This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. Cataloged from PDF version of thesis report. Includes bibliographical references (page 41-42). Tuberculosis 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. Nahid Kamal Subrina Islam Al Faysal Bin Asad Sumaiya Khatun B. Computer Science and Engineering 2017-12-27T04:51:00Z 2017-12-27T04:51:00Z 2017 2017 Thesis ID 12201058 ID 13301139 ID 13101095 ID 12201099 http://hdl.handle.net/10361/8716 en BRAC University thesis 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. 42 pages application/pdf BRAC University
institution	Brac University
collection	Institutional Repository
language	English
topic	Tuberculosis Ziehl-Neelsen stain Bayesian segmentation Tuberculosis objects Photomicrographic calibration Image processing
spellingShingle	Tuberculosis Ziehl-Neelsen stain Bayesian segmentation Tuberculosis objects Photomicrographic calibration Image processing Kamal, Nahid Islam, Subrina Asad, Al Faysal Bin Khatun, Sumaiya Tuberculosis diagnosis through image processing
description	This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.
author2	Chakrabarty, Dr. Amitabha
author_facet	Chakrabarty, Dr. Amitabha Kamal, Nahid Islam, Subrina Asad, Al Faysal Bin Khatun, Sumaiya
format	Thesis
author	Kamal, Nahid Islam, Subrina Asad, Al Faysal Bin Khatun, Sumaiya
author_sort	Kamal, Nahid
title	Tuberculosis diagnosis through image processing
title_short	Tuberculosis diagnosis through image processing
title_full	Tuberculosis diagnosis through image processing
title_fullStr	Tuberculosis diagnosis through image processing
title_full_unstemmed	Tuberculosis diagnosis through image processing
title_sort	tuberculosis diagnosis through image processing
publisher	BRAC University
publishDate	2017
url	http://hdl.handle.net/10361/8716
work_keys_str_mv	AT kamalnahid tuberculosisdiagnosisthroughimageprocessing AT islamsubrina tuberculosisdiagnosisthroughimageprocessing AT asadalfaysalbin tuberculosisdiagnosisthroughimageprocessing AT khatunsumaiya tuberculosisdiagnosisthroughimageprocessing
_version_	1814307858299224064

Tuberculosis diagnosis through image processing

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