An active contour model for medical image segmentation with application to brain CT image Article Swipe
Xiaohua Qian
,
Jiahui Wang
,
Shuxu Guo
,
Qiang Li
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.17615/tztc-b913
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.17615/tztc-b913
Cerebrospinal fluid (CSF) segmentation in computed tomography (CT) is a key step in computer-aided detection (CAD) of acute ischemic stroke. Because of image noise, low contrast and intensity inhomogeneity, CSF segmentation has been a challenging task. A region-based active contour model, which is insensitive to contour initialization and robust to intensity inhomogeneity, was developed for segmenting CSF in brain CT images.
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- en
- Landing Page
- https://doi.org/10.17615/tztc-b913
- OA Status
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4299601127Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.17615/tztc-b913Digital Object Identifier
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An active contour model for medical image segmentation with application to brain CT imageWork title
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articleOpenAlex work type
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enPrimary language
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2020Year of publication
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2020-11-05Full publication date if available
- Authors
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Xiaohua Qian, Jiahui Wang, Shuxu Guo, Qiang LiList of authors in order
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https://doi.org/10.17615/tztc-b913Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://doi.org/10.17615/tztc-b913Direct OA link when available
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Active contour model, Artificial intelligence, Computer vision, Image (mathematics), Computer science, Image segmentation, Pattern recognition (psychology)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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