Please use this identifier to cite or link to this item:
https://ptsldigital.ukm.my/jspui/handle/123456789/578149
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Nurwahidah M (UITM) | |
dc.contributor.author | Wan E. Z. W. A. R (UITM) | |
dc.contributor.author | Shaharuddin C. S (UITM) | |
dc.date.accessioned | 2023-11-06T02:58:46Z | - |
dc.date.available | 2023-11-06T02:58:46Z | - |
dc.date.issued | 2018-01 | |
dc.identifier.issn | 0128-7680 | |
dc.identifier.other | ukmvital:98138 | |
dc.identifier.uri | https://ptsldigital.ukm.my/jspui/handle/123456789/578149 | - |
dc.description | This paper presents the application of active contours region-based method of image segmentation to Computed Tomography (CT) images. Previous researchers applied this region based method on Magnetic Resonance Image (MRI), in vivo images and synthetic images which contain intensity inhomogeneities. In this paper, a different modality known as Computed Tomography (CT) scan was applied. CT scan also produces images containing intensity inhomogeneity, and it is predicted that this method provide good segmentation results. The main objective of applying this method is to check its applicability on CT images. The segmentation process begins by finding the area of interest (black region). Results from this experiment are then used in estimating time of death. Experimental results show that this method has successfully segmented the black region when some parameters changed, provided that the regions are closed to each other. If the black regions are located far from each other, then this method will only segment certain areas. | |
dc.language.iso | en | |
dc.publisher | Universiti Putra Malaysia Press | |
dc.relation.haspart | Pertanika Journals | |
dc.relation.uri | http://www.pertanika.upm.edu.my/regular_issues.php?jtype=2&journal=JST-26-1-1 | |
dc.rights | UKM | |
dc.subject | Local Gaussian distribution | |
dc.subject | Computed tomography images | |
dc.subject | Segmentation | |
dc.title | Application of active contours driven by local gaussian distribution fitting energy to the computed tomography images | |
dc.type | Journal Article | |
dc.format.volume | 26 | |
dc.format.pages | 309-316 | |
dc.format.issue | 1 | |
Appears in Collections: | Journal Content Pages/ Kandungan Halaman Jurnal |
Files in This Item:
File | Description | Size | Format | |
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ukmvital_98138+Source01+Source010.PDF | 1.33 MB | Adobe PDF | View/Open |
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