Segmentation Of Ultisequence Medical Images Using Random Walks Algorithm And Rough Sets Theory

Segmentation Of Ultisequence Medical Images Using Random Walks Algorithm And Rough Sets Theory

Segmentasi imej Magnetic Resonance (MR) merupakan satu tugas klinikal yang mencabar. Selalunya, satu jenis imej MR tidak mencukupi untuk memberikan maklumat yang lengkap mengenai sesuatu tisu patologi atau objek visual dari imej Accurate Magnetic Resonance (MR) image segmentation is a clinically...

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Main Author: Lim, Khai Yin
Format: Thesis
Language:English
Published: 2017
Subjects:
QA75.5-76.95 Electronic computers
Computer science
Online Access:http://eprints.usm.my/38873/1/Segmentation_of_multisequence_medical_images_using_random_walks_algorithm_and_rough_sets_theory_by_Lim_Khai_Yin..pdf
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id my-usm-ep.38873
record_format uketd_dc
spelling my-usm-ep.388732019-04-12T05:24:59Z Segmentation Of Ultisequence Medical Images Using Random Walks Algorithm And Rough Sets Theory 2017-07 Lim, Khai Yin QA75.5-76.95 Electronic computers. Computer science Segmentasi imej Magnetic Resonance (MR) merupakan satu tugas klinikal yang mencabar. Selalunya, satu jenis imej MR tidak mencukupi untuk memberikan maklumat yang lengkap mengenai sesuatu tisu patologi atau objek visual dari imej Accurate Magnetic Resonance (MR) image segmentation is a clinically challenging task. More often than not, one type of MRI image is insufficient to provide the complete information about a pathological tissue or a visual object from the image 2017-07 Thesis http://eprints.usm.my/38873/ http://eprints.usm.my/38873/1/Segmentation_of_multisequence_medical_images_using_random_walks_algorithm_and_rough_sets_theory_by_Lim_Khai_Yin..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 QA75.5-76.95 Electronic computers
Computer science
spellingShingle QA75.5-76.95 Electronic computers
Computer science
Lim, Khai Yin
Segmentation Of Ultisequence Medical Images Using Random Walks Algorithm And Rough Sets Theory
description Segmentasi imej Magnetic Resonance (MR) merupakan satu tugas klinikal yang mencabar. Selalunya, satu jenis imej MR tidak mencukupi untuk memberikan maklumat yang lengkap mengenai sesuatu tisu patologi atau objek visual dari imej Accurate Magnetic Resonance (MR) image segmentation is a clinically challenging task. More often than not, one type of MRI image is insufficient to provide the complete information about a pathological tissue or a visual object from the image
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Lim, Khai Yin
author_facet Lim, Khai Yin
author_sort Lim, Khai Yin
title Segmentation Of Ultisequence Medical Images Using Random Walks Algorithm And Rough Sets Theory
title_short Segmentation Of Ultisequence Medical Images Using Random Walks Algorithm And Rough Sets Theory
title_full Segmentation Of Ultisequence Medical Images Using Random Walks Algorithm And Rough Sets Theory
title_fullStr Segmentation Of Ultisequence Medical Images Using Random Walks Algorithm And Rough Sets Theory
title_full_unstemmed Segmentation Of Ultisequence Medical Images Using Random Walks Algorithm And Rough Sets Theory
title_sort segmentation of ultisequence medical images using random walks algorithm and rough sets theory
granting_institution Universiti Sains Malaysia
granting_department Pusat Pengajian Sains Komputer
publishDate 2017
url http://eprints.usm.my/38873/1/Segmentation_of_multisequence_medical_images_using_random_walks_algorithm_and_rough_sets_theory_by_Lim_Khai_Yin..pdf
_version_ 1747820710380699648

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