An Improved Level Set Algorithm for Prostate Region Segmentation Article Swipe
Shiju Yan
,
Yi Han
,
Guangyu Tang
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.11938/cjmr20212885
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.11938/cjmr20212885
Accurate segmentation of prostate region is an important prerequisite to improve the accuracy of computer-aided prostate cancer diagnosis. In this work, a new and accurate prostate segmentation algorithm is proposed and tested. The new algorithm consists of 4 steps: reading T2-weighted magnetic resonance images, calculating local binary pattern (LBP) feature map of prostate magnetic resonance images by using an 8x5 LBP feature template, segmenting the feature map with the improved distance regularization level set evolution (DRLSE) algorithm, and extracting coarse contour of the prostate. A new energy function is constructed to extract local gray scale information and gradient information, and the coarse contour is iteratively developed into the final fine prostate contour on the basis of this new energy function. The algorithm was tested with the SPIE-AAPM-NCI Prostate MR Classification Challenge Database. The segmentation results of the proposed algorithm were compared with that of manual segmentation by doctors. The results showed that the Dice coefficient obtained by using the proposed algorithm was 0.94±0.01, with a relative volume difference (RVD) of -1.21%±2.44% and a 95% Hausdorff distance (HD) of 6.15±0.66 mm. Compared with the existing segmentation algorithms, the segmentation results obtained with the algorithm proposed in this paper are closer to the manual segmentation results.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doaj.org/article/8d86fc59e3414698b858e59170b235af
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4405929246
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4405929246Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.11938/cjmr20212885Digital Object Identifier
- Title
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An Improved Level Set Algorithm for Prostate Region SegmentationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-09-01Full publication date if available
- Authors
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Shiju Yan, Yi Han, Guangyu TangList of authors in order
- Landing page
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https://doaj.org/article/8d86fc59e3414698b858e59170b235afPublisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://doaj.org/article/8d86fc59e3414698b858e59170b235afDirect OA link when available
- Concepts
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Segmentation, Algorithm, Set (abstract data type), Computer science, Artificial intelligence, Pattern recognition (psychology), Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2023: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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