Knowledge Guided Automatic Contour Initialization And Segmentation Of Abdominal Structures In CT Images

Computed Tomography (CT) scans are becoming a priceless means of diagnosing abdominal structures. CT scans result in a huge number of 2D slices of the acquired anatomical part in abdominal imaging. CT are more preferred compared to sensitive imaging techniques such as MRI in abdominal imaging owi...

Full description

Saved in:

Bibliographic Details
Main Author:	Jawarneh, Mahmoud Saleh Mahmoud
Format:	Thesis
Language:	English
Published:	2012
Subjects:	QA1 Mathematics (General)
Online Access:	http://eprints.usm.my/45658/1/MAHMOUD%20SALEH%20MAHMOUD%20JAWARNEH_HJ.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-usm-ep.45658
record_format	uketd_dc
spelling	my-usm-ep.456582019-10-15T07:54:21Z Knowledge Guided Automatic Contour Initialization And Segmentation Of Abdominal Structures In CT Images 2012-02 Jawarneh, Mahmoud Saleh Mahmoud QA1 Mathematics (General) Computed Tomography (CT) scans are becoming a priceless means of diagnosing abdominal structures. CT scans result in a huge number of 2D slices of the acquired anatomical part in abdominal imaging. CT are more preferred compared to sensitive imaging techniques such as MRI in abdominal imaging owing to their high signal to noise and good spatial resolution. In the area of medical image processing, the current interests are in the automated analysis and visualization of liver, spleen, and kidney to assist in diagnosis, radiation therapy planning and surgical planning. Delineation of these structures which is still an open research problem is the first and fundamental step in all of these studies. Automation of medical image segmentation reduces time-consuming, tedious, subjective human interaction tasks and may aid radiologists, who are normally required to view thousands of images daily. Thus, automatic segmentation is the main focus of several research efforts. In this research, we propose an automatic knowledge-based segmentation framework based on active contour methods. The proposed segmentation system is generic, and employs multiple sources of medical knowledge: medical atlas; expert’s rules; multiple views: axial, coronal and sagittal; image features and image DICOM Meta data. The focus in this research is on level set active contour segmentation methods which provide promising results, robust to dataset variations and do not require extensive prior training. As such, they can be reliably used for segmentation of major structures in abdominal CT scans. The obtained results are very promising showing significant improvements over other methods where the volume measurements error is 7% and the processing time was improved by 68%. 2012-02 Thesis http://eprints.usm.my/45658/ http://eprints.usm.my/45658/1/MAHMOUD%20SALEH%20MAHMOUD%20JAWARNEH_HJ.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Komputer
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA1 Mathematics (General)
spellingShingle	QA1 Mathematics (General) Jawarneh, Mahmoud Saleh Mahmoud Knowledge Guided Automatic Contour Initialization And Segmentation Of Abdominal Structures In CT Images
description	Computed Tomography (CT) scans are becoming a priceless means of diagnosing abdominal structures. CT scans result in a huge number of 2D slices of the acquired anatomical part in abdominal imaging. CT are more preferred compared to sensitive imaging techniques such as MRI in abdominal imaging owing to their high signal to noise and good spatial resolution. In the area of medical image processing, the current interests are in the automated analysis and visualization of liver, spleen, and kidney to assist in diagnosis, radiation therapy planning and surgical planning. Delineation of these structures which is still an open research problem is the first and fundamental step in all of these studies. Automation of medical image segmentation reduces time-consuming, tedious, subjective human interaction tasks and may aid radiologists, who are normally required to view thousands of images daily. Thus, automatic segmentation is the main focus of several research efforts. In this research, we propose an automatic knowledge-based segmentation framework based on active contour methods. The proposed segmentation system is generic, and employs multiple sources of medical knowledge: medical atlas; expert’s rules; multiple views: axial, coronal and sagittal; image features and image DICOM Meta data. The focus in this research is on level set active contour segmentation methods which provide promising results, robust to dataset variations and do not require extensive prior training. As such, they can be reliably used for segmentation of major structures in abdominal CT scans. The obtained results are very promising showing significant improvements over other methods where the volume measurements error is 7% and the processing time was improved by 68%.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Jawarneh, Mahmoud Saleh Mahmoud
author_facet	Jawarneh, Mahmoud Saleh Mahmoud
author_sort	Jawarneh, Mahmoud Saleh Mahmoud
title	Knowledge Guided Automatic Contour Initialization And Segmentation Of Abdominal Structures In CT Images
title_short	Knowledge Guided Automatic Contour Initialization And Segmentation Of Abdominal Structures In CT Images
title_full	Knowledge Guided Automatic Contour Initialization And Segmentation Of Abdominal Structures In CT Images
title_fullStr	Knowledge Guided Automatic Contour Initialization And Segmentation Of Abdominal Structures In CT Images
title_full_unstemmed	Knowledge Guided Automatic Contour Initialization And Segmentation Of Abdominal Structures In CT Images
title_sort	knowledge guided automatic contour initialization and segmentation of abdominal structures in ct images
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Sains Komputer
publishDate	2012
url	http://eprints.usm.my/45658/1/MAHMOUD%20SALEH%20MAHMOUD%20JAWARNEH_HJ.pdf
_version_	1747821540908466176

Knowledge Guided Automatic Contour Initialization And Segmentation Of Abdominal Structures In CT Images

Similar Items