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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| 格式: | Thesis |
| 語言: | 英语 |
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2017
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| 在線閱讀: | http://eprints.usm.my/38873/ |
| Abstract | Abstract here |
| _version_ | 1855629578918166528 |
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| author | Lim, Khai Yin |
| author_facet | Lim, Khai Yin |
| author_sort | Lim, Khai Yin |
| 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
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| first_indexed | 2025-10-17T08:12:54Z |
| format | Thesis |
| id | usm-38873 |
| institution | Universiti Sains Malaysia |
| language | English |
| last_indexed | 2025-10-17T08:12:54Z |
| publishDate | 2017 |
| record_format | EPrints |
| record_pdf | Restricted |
| spelling | usm-388732019-04-12T05:24:59Z http://eprints.usm.my/38873/ Segmentation Of Ultisequence Medical Images Using Random Walks Algorithm And Rough Sets Theory 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 NonPeerReviewed application/pdf en http://eprints.usm.my/38873/1/Segmentation_of_multisequence_medical_images_using_random_walks_algorithm_and_rough_sets_theory_by_Lim_Khai_Yin..pdf Lim, Khai Yin (2017) Segmentation Of Ultisequence Medical Images Using Random Walks Algorithm And Rough Sets Theory. PhD thesis, Universiti Sains Malaysia. |
| 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 |
| thesis_level | PhD |
| title | 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_short | 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 |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://eprints.usm.my/38873/ |
| work_keys_str_mv | AT limkhaiyin segmentationofultisequencemedicalimagesusingrandomwalksalgorithmandroughsetstheory |