Abstract:
:A rule-based, low-level segmentation system that can automatically identify the space occupied by different structures of the brain by magnetic resonance imaging (MRI) is described. Given three-dimensional image data as a stack of slices, it can extract brain parenchyma, cerebro-spinal fluid, and high-intensity abnormalities. The multiple feature environment of MR imaging is used to comput several low-level features to enhance the separability of voxels of different structures. The population distribution of each feature is considered and a confidence function is computed whose amplitude indicates the likelihood of a voxel, with a given feature value, being a member of a class of voxels. Confidence levels are divided into a set of ranges to define notions such as highly confident, moderately confident, and least confident. The rule-based system consists of a set of sequential stages in which partially segmented binary scenes of one stage guide the next stage. Some important low-level definitions and rules for a clinical imaging protocol are presented. The system is applied to several MR images.
journal_name
IEEE Trans Med Imagingjournal_title
IEEE transactions on medical imagingauthors
Raya SPdoi
10.1109/42.57771subject
Has Abstractpub_date
1990-01-01 00:00:00pages
327-37issue
3eissn
0278-0062issn
1558-254Xjournal_volume
9pub_type
杂志文章abstract::The interest of compressive sampling in ultrasound imaging has been recently extensively evaluated by several research teams. Following the different application setups, it has been shown that the RF data may be reconstructed from a small number of measurements and/or using a reduced number of ultrasound pulse emissio...
journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/TMI.2015.2493241
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/TMI.2016.2646518
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/TMI.2010.2059709
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/42.56340
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journal_title:IEEE transactions on medical imaging
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
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pub_type: 杂志文章
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/42.746626
更新日期:1998-12-01 00:00:00
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/TMI.2009.2033597
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/TMI.2018.2870939
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/TMI.2018.2829934
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/TMI.2013.2284657
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
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pub_type: 杂志文章
doi:10.1109/TMI.2003.815069
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/42.387718
更新日期:1995-01-01 00:00:00
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/TMI.2018.2823768
更新日期:2018-06-01 00:00:00
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/TMI.1984.4307681
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
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journal_title:IEEE transactions on medical imaging
pub_type: 社论
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/TMI.2009.2012852
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
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journal_title:IEEE transactions on medical imaging
pub_type: 信件
doi:10.1109/42.832961
更新日期:2000-01-01 00:00:00
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/TMI.2007.902802
更新日期:2008-01-01 00:00:00
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
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