Novel level set based statistical frameworks for segmentation of MR images

In summary, two automated frameworks for segmentation of medical images are proposed. They are the joint curve evolution and the EM-joint shape based algorithms. In addition, the generalization of our frameworks to 3D models of multiple struc- tures. The resulting implementation is tested on a varie...

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Main Author: Mahshid Farzinfar
Other Authors: Teoh Eam Khwang
Format: Theses and Dissertations
Language:English
Published: 2012
Subjects:
Online Access:https://hdl.handle.net/10356/50726
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-507262023-07-04T17:09:18Z Novel level set based statistical frameworks for segmentation of MR images Mahshid Farzinfar Teoh Eam Khwang School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems In summary, two automated frameworks for segmentation of medical images are proposed. They are the joint curve evolution and the EM-joint shape based algorithms. In addition, the generalization of our frameworks to 3D models of multiple struc- tures. The resulting implementation is tested on a variety of studies to parceling of anatomical structures. The proposed algorithms can be used for surgery navigation and 3D visualization. They could also be applied to neuroscience studies in finding new diseases related to anatomical characteristics and the increase in reliability in diagnosing of illnesses such as schizophrenia. DOCTOR OF PHILOSOPHY (EEE) 2012-09-24T05:42:51Z 2012-09-24T05:42:51Z 2012 2012 Thesis Mahshid, F. (2012). Novel level set based statistical frameworks for segmentation of MR images. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/50726 10.32657/10356/50726 en 202 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Mahshid Farzinfar
Novel level set based statistical frameworks for segmentation of MR images
description In summary, two automated frameworks for segmentation of medical images are proposed. They are the joint curve evolution and the EM-joint shape based algorithms. In addition, the generalization of our frameworks to 3D models of multiple struc- tures. The resulting implementation is tested on a variety of studies to parceling of anatomical structures. The proposed algorithms can be used for surgery navigation and 3D visualization. They could also be applied to neuroscience studies in finding new diseases related to anatomical characteristics and the increase in reliability in diagnosing of illnesses such as schizophrenia.
author2 Teoh Eam Khwang
author_facet Teoh Eam Khwang
Mahshid Farzinfar
format Theses and Dissertations
author Mahshid Farzinfar
author_sort Mahshid Farzinfar
title Novel level set based statistical frameworks for segmentation of MR images
title_short Novel level set based statistical frameworks for segmentation of MR images
title_full Novel level set based statistical frameworks for segmentation of MR images
title_fullStr Novel level set based statistical frameworks for segmentation of MR images
title_full_unstemmed Novel level set based statistical frameworks for segmentation of MR images
title_sort novel level set based statistical frameworks for segmentation of mr images
publishDate 2012
url https://hdl.handle.net/10356/50726
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