Automated Classification and Annotation of Computed Tomography Brain Images

Brain hemorrhage detection is clinically crucial for the patients having head trauma and neurological disturbances. Early finding and accurate diagnosis of the brain abnormalities is one of the key contributions for the execution of the successful therapy and proper treatment. Multi-slice Computed T...

Full description

Saved in:

Bibliographic Details
Main Author:	Tong, Hau Lee
Format:	Thesis
Published:	2015
Subjects:	R856-857 Biomedical engineering Electronics Instrumentation
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-mmu-ep.6854
record_format	uketd_dc
spelling	my-mmu-ep.68542017-07-12T03:46:39Z Automated Classification and Annotation of Computed Tomography Brain Images 2015-09 Tong, Hau Lee R856-857 Biomedical engineering. Electronics. Instrumentation Brain hemorrhage detection is clinically crucial for the patients having head trauma and neurological disturbances. Early finding and accurate diagnosis of the brain abnormalities is one of the key contributions for the execution of the successful therapy and proper treatment. Multi-slice Computed Tomograph (CT) scans are widely employed in today’s examination of head traumas due to its effectiveness to disclose some abnormalities such as brain hemorrhages and so on. However, radiologists have to manually analyse the CT slices for the presence of brain hemorrhages. Due to the large volume of CT scan examinations, it is important to develop a computerised system that can assist the radiologists to automatically detect the presence of the brain abnormalities as well as automatically retrieve the images. This thesis presents an automated annotation and classification of the CT brain images. The main objective is to propose a new methodology to annotate and classify the different types of brain hemorrhages which are intra-axial, subdural and extradural hemorrhages. Besides, this thesis also aims to evaluate and investigate the effectiveness and suitability of different segmentation and classification techniques as well as introduce the new features for the classification. 2015-09 Thesis http://shdl.mmu.edu.my/6854/ http://library.mmu.edu.my/diglib/onlinedb/dig_lib.php phd doctoral Multimedia University Faculty of Computing and Informatics
institution	Multimedia University
collection	MMU Institutional Repository
topic	R856-857 Biomedical engineering Electronics Instrumentation
spellingShingle	R856-857 Biomedical engineering Electronics Instrumentation Tong, Hau Lee Automated Classification and Annotation of Computed Tomography Brain Images
description	Brain hemorrhage detection is clinically crucial for the patients having head trauma and neurological disturbances. Early finding and accurate diagnosis of the brain abnormalities is one of the key contributions for the execution of the successful therapy and proper treatment. Multi-slice Computed Tomograph (CT) scans are widely employed in today’s examination of head traumas due to its effectiveness to disclose some abnormalities such as brain hemorrhages and so on. However, radiologists have to manually analyse the CT slices for the presence of brain hemorrhages. Due to the large volume of CT scan examinations, it is important to develop a computerised system that can assist the radiologists to automatically detect the presence of the brain abnormalities as well as automatically retrieve the images. This thesis presents an automated annotation and classification of the CT brain images. The main objective is to propose a new methodology to annotate and classify the different types of brain hemorrhages which are intra-axial, subdural and extradural hemorrhages. Besides, this thesis also aims to evaluate and investigate the effectiveness and suitability of different segmentation and classification techniques as well as introduce the new features for the classification.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Tong, Hau Lee
author_facet	Tong, Hau Lee
author_sort	Tong, Hau Lee
title	Automated Classification and Annotation of Computed Tomography Brain Images
title_short	Automated Classification and Annotation of Computed Tomography Brain Images
title_full	Automated Classification and Annotation of Computed Tomography Brain Images
title_fullStr	Automated Classification and Annotation of Computed Tomography Brain Images
title_full_unstemmed	Automated Classification and Annotation of Computed Tomography Brain Images
title_sort	automated classification and annotation of computed tomography brain images
granting_institution	Multimedia University
granting_department	Faculty of Computing and Informatics
publishDate	2015
_version_	1747829637250023424

Automated Classification and Annotation of Computed Tomography Brain Images

Similar Items