Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique

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

Bibliografiska uppgifter
Huvudupphovsmän:	Shakir, Mohsinul Bari, Hossain, Mohammad Amzad, Shams, Khan Mohammad Aymaan, Akib, Faisal Raihan
Övriga upphovsmän:	Alam, Dr. Md. Ashraful
Materialtyp:	Lärdomsprov
Språk:	English
Publicerad:	BRAC University 2018
Ämnen:	Segmentation Quantification Artery blockage Coronary blockage Image processing technique
Länkar:	http://hdl.handle.net/10361/9495

id	10361-9495
record_format	dspace
spelling	10361-94952022-01-26T10:18:24Z Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique Shakir, Mohsinul Bari Hossain, Mohammad Amzad Shams, Khan Mohammad Aymaan Akib, Faisal Raihan Alam, Dr. Md. Ashraful Department of Computer Science and Engineering, BRAC University Segmentation Quantification Artery blockage Coronary blockage Image processing technique This thesis report is submitted in partial fulfilment 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 (pages 50-53). Advancements in computing speed and power have made revolutionary changes in medical science practices and this is no different for cardiology. Such advancements in computer sciences have made the existing medical tests of heart into being. These tests are: ECG, CTA, & Echocardiogram. CTA (Computed Tomography Angiography) is a widely used imaging technique to visualize arterial and venous vessels throughout the body. In clinical practice, the analysis mainly relies on visual inspection or manual measurements by experienced cardiologists. The proposed method aims towards a full automation of the detection of coronary artery blockage through some image processing techniques so that the system does not have to rely on any human’s inspection. The goal of the research is to implement the proposed image processing techniques so that the system can detect the narrowing area of the wall of coronary arteries due to the condensation of different artery blocking agents. This detection is crucial for further analysis of the heart. The research suggests that the system will require a 64-slice CTA image as input. After the acquisition of the desired input image, it will go through several steps to determine the region of interest. This research proposes a two stage approach that includes the pre-processing stage and decision stage. The pre-processing stage involves common image processing strategies while the decision stage involves the extraction and calculation of two feature ratios to finally determine the intended result. In order to get more insights of the subject of these examinations, this research has proposed the use of an algorithm to create a 3-D model. Moreover, the system to work more precisely and effectively, use of several techniques have been suggested including parallel processing with shared memory allocation between the CPU and the GPU. Using the parallel processing technique not only makes the whole process at least 7 times faster, but also helps several stages of the process work more effectively. Mohsinul Bari Shakir Mohammad Amzad Hossain Khan Mohammad Aymaan Shams Faisal Raihan Akib Department of Computer Science and Engineering, BRAC University. B. Computer Science and Engineering 2018-02-18T05:20:57Z 2018-02-18T05:20:57Z 2017 2017 Thesis ID 13101068 ID 13101016 ID 13101072 ID 13101204 http://hdl.handle.net/10361/9495 en BRAC University thesis reports 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. 53 pages application/pdf BRAC University
institution	Brac University
collection	Institutional Repository
language	English
topic	Segmentation Quantification Artery blockage Coronary blockage Image processing technique
spellingShingle	Segmentation Quantification Artery blockage Coronary blockage Image processing technique Shakir, Mohsinul Bari Hossain, Mohammad Amzad Shams, Khan Mohammad Aymaan Akib, Faisal Raihan Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique
description	This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.
author2	Alam, Dr. Md. Ashraful
author_facet	Alam, Dr. Md. Ashraful Shakir, Mohsinul Bari Hossain, Mohammad Amzad Shams, Khan Mohammad Aymaan Akib, Faisal Raihan
format	Thesis
author	Shakir, Mohsinul Bari Hossain, Mohammad Amzad Shams, Khan Mohammad Aymaan Akib, Faisal Raihan
author_sort	Shakir, Mohsinul Bari
title	Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique
title_short	Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique
title_full	Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique
title_fullStr	Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique
title_full_unstemmed	Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique
title_sort	early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique
publisher	BRAC University
publishDate	2018
url	http://hdl.handle.net/10361/9495
work_keys_str_mv	AT shakirmohsinulbari earlydetectionsegmentationandquantificationofcoronaryarteryblockageusingefficientimageprocessingtechnique AT hossainmohammadamzad earlydetectionsegmentationandquantificationofcoronaryarteryblockageusingefficientimageprocessingtechnique AT shamskhanmohammadaymaan earlydetectionsegmentationandquantificationofcoronaryarteryblockageusingefficientimageprocessingtechnique AT akibfaisalraihan earlydetectionsegmentationandquantificationofcoronaryarteryblockageusingefficientimageprocessingtechnique
_version_	1814308945023467520

Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique

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