Liver Isolation in Abdominal MRI
[1] Cloud fields retrieved from remotely sensed satellite data resemble functions depicting spectral values at each spatial position (x, y). Segmenting such cloud fields through a simple thresholding technique may not provide any structurally significant information about each segmented category. An...
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AMER GEOPHYSICAL UNION
2008
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| Online Access: | http://shdl.mmu.edu.my/2290/ |
| _version_ | 1848790016251133952 |
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| author | Logeswaran, Rajasvaran Haw, Tan Wooi Sarker, Shakowat Zaman |
| author_facet | Logeswaran, Rajasvaran Haw, Tan Wooi Sarker, Shakowat Zaman |
| author_sort | Logeswaran, Rajasvaran |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | [1] Cloud fields retrieved from remotely sensed satellite data resemble functions depicting spectral values at each spatial position (x, y). Segmenting such cloud fields through a simple thresholding technique may not provide any structurally significant information about each segmented category. An approach based on the use of multiscale convexity analysis to derive structurally significant regions from cloud fields is addressed in this paper. This analysis requires (1) the generation of cloud fields at coarser resolutions and (2) the construction of convex hulls of cloud fields, at corresponding resolutions by employing multiscale morphologic opening transformation and half-plane closings with certain logical operations. The three basic parameters required from these generated multiscale phenomena in order to accomplish the structure-based segmentation include (1) the areas of multiscale cloud fields, (2) the areas of corresponding convex hulls, and (3) the estimation of convexity measures at corresponding resolutions by employing the areas of cloud fields and areas of corresponding convex hulls. These convexity measures computed for multiscale cloud fields are plotted as a function of the resolution imposed owing to multiscale opening to derive a causal relationship. The scaling exponents derived from these graphical plots are taken as the basis for (1) determining the transition zones between the regimes and (2) segmenting the cloud fields into morphologically significant regions. We demonstrated this approach on two different cloud fields retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) data. The segmented regions from these cloud fields possess different degrees of spatial complexities. As many macroscale and microscale atmospheric fields are classified according to spatial variability indexes, the framework proposed here would supplement those existing atmospheric field classification methodologies. |
| first_indexed | 2025-11-14T18:05:54Z |
| format | Article |
| id | mmu-2290 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:05:54Z |
| publishDate | 2008 |
| publisher | AMER GEOPHYSICAL UNION |
| recordtype | eprints |
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| spelling | mmu-22902011-08-25T00:45:47Z http://shdl.mmu.edu.my/2290/ Liver Isolation in Abdominal MRI Logeswaran, Rajasvaran Haw, Tan Wooi Sarker, Shakowat Zaman RA1001-1171 Forensic medicine. Medical jurisprudence. Legal medicine RA421-790.95 Public health. Hygiene. Preventive medicine [1] Cloud fields retrieved from remotely sensed satellite data resemble functions depicting spectral values at each spatial position (x, y). Segmenting such cloud fields through a simple thresholding technique may not provide any structurally significant information about each segmented category. An approach based on the use of multiscale convexity analysis to derive structurally significant regions from cloud fields is addressed in this paper. This analysis requires (1) the generation of cloud fields at coarser resolutions and (2) the construction of convex hulls of cloud fields, at corresponding resolutions by employing multiscale morphologic opening transformation and half-plane closings with certain logical operations. The three basic parameters required from these generated multiscale phenomena in order to accomplish the structure-based segmentation include (1) the areas of multiscale cloud fields, (2) the areas of corresponding convex hulls, and (3) the estimation of convexity measures at corresponding resolutions by employing the areas of cloud fields and areas of corresponding convex hulls. These convexity measures computed for multiscale cloud fields are plotted as a function of the resolution imposed owing to multiscale opening to derive a causal relationship. The scaling exponents derived from these graphical plots are taken as the basis for (1) determining the transition zones between the regimes and (2) segmenting the cloud fields into morphologically significant regions. We demonstrated this approach on two different cloud fields retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) data. The segmented regions from these cloud fields possess different degrees of spatial complexities. As many macroscale and microscale atmospheric fields are classified according to spatial variability indexes, the framework proposed here would supplement those existing atmospheric field classification methodologies. AMER GEOPHYSICAL UNION 2008-08 Article NonPeerReviewed Logeswaran, Rajasvaran and Haw, Tan Wooi and Sarker, Shakowat Zaman (2008) Liver Isolation in Abdominal MRI. Journal of Medical Systems, 32 (4). pp. 259-268. ISSN 0148-5598 http://dx.doi.org/10.1007/s10916-008-9131-2 doi:10.1007/s10916-008-9131-2 doi:10.1007/s10916-008-9131-2 |
| spellingShingle | RA1001-1171 Forensic medicine. Medical jurisprudence. Legal medicine RA421-790.95 Public health. Hygiene. Preventive medicine Logeswaran, Rajasvaran Haw, Tan Wooi Sarker, Shakowat Zaman Liver Isolation in Abdominal MRI |
| title | Liver Isolation in Abdominal MRI |
| title_full | Liver Isolation in Abdominal MRI |
| title_fullStr | Liver Isolation in Abdominal MRI |
| title_full_unstemmed | Liver Isolation in Abdominal MRI |
| title_short | Liver Isolation in Abdominal MRI |
| title_sort | liver isolation in abdominal mri |
| topic | RA1001-1171 Forensic medicine. Medical jurisprudence. Legal medicine RA421-790.95 Public health. Hygiene. Preventive medicine |
| url | http://shdl.mmu.edu.my/2290/ http://shdl.mmu.edu.my/2290/ http://shdl.mmu.edu.my/2290/ |