A Learning Approach for Suture Thread Detection With Feature Enhancement and Segmentation for 3-D Shape Reconstruction Article Swipe
Bo Lu
,
Xiaoqing Yu
,
Jianhui Lai
,
Kaicheng Huang
,
Keith Chan
,
Henry K. Chu
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1109/tase.2019.2950005
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1109/tase.2019.2950005
A vision-based system presents one of the most reliable methods for achieving an automated robot-assisted manipulation associated with surgical knot tying. However, some challenges in suture thread detection and automated suture thread grasping significantly hinder the realization of a fully automated surgical knot tying. In this article, we propose a novel algorithm that can be used for computing the 3-D coordinates of a suture thread in knot tying. After proper training with our data set, we built a deep-learning model for accurately locating the suture's tip. By applying a Hessian-based filter with multiscale parameters, the environmental noises can be eliminated while preserving the suture thread information. A multistencils fast marching method was then employed to segment the suture thread, and a precise stereomatching algorithm was implemented to compute the 3-D coordinates of this thread. Experiments associated with the precision of the deep-learning model, the robustness of the 2-D segmentation approach, and the overall accuracy of 3-D coordinate computation of the suture thread were conducted in various scenarios, and the results quantitatively validate the feasibility and reliability of the entire scheme for automated 3-D shape reconstruction.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/tase.2019.2950005
- OA Status
- green
- Cited By
- 21
- References
- 45
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2990444195
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2990444195Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/tase.2019.2950005Digital Object Identifier
- Title
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A Learning Approach for Suture Thread Detection With Feature Enhancement and Segmentation for 3-D Shape ReconstructionWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2019Year of publication
- Publication date
-
2019-11-26Full publication date if available
- Authors
-
Bo Lu, Xiaoqing Yu, Jianhui Lai, Kaicheng Huang, Keith Chan, Henry K. ChuList of authors in order
- Landing page
-
https://doi.org/10.1109/tase.2019.2950005Publisher 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://ira.lib.polyu.edu.hk/bitstream/10397/106380/1/Lu_Learning_Approach_Suture.pdfDirect OA link when available
- Concepts
-
Thread (computing), Computer science, Artificial intelligence, Computer vision, Segmentation, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
21Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 2, 2023: 4, 2022: 6, 2021: 5, 2020: 4Per-year citation counts (last 5 years)
- References (count)
-
45Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W2012872284, https://openalex.org/W2129534965, https://openalex.org/W2156155065, https://openalex.org/W2169733476, https://openalex.org/W2111204664, https://openalex.org/W1977946246, https://openalex.org/W2022649923, https://openalex.org/W1555173571, https://openalex.org/W2109200236, https://openalex.org/W1964620727, https://openalex.org/W4236020996, https://openalex.org/W2341108136, https://openalex.org/W2738671059, https://openalex.org/W2601943843, https://openalex.org/W2000462596, https://openalex.org/W6664906822, https://openalex.org/W2744900881, https://openalex.org/W2156040158, https://openalex.org/W1989408822, https://openalex.org/W2090026077, https://openalex.org/W2158308356, https://openalex.org/W2037988980, https://openalex.org/W2973945662, https://openalex.org/W104801099, https://openalex.org/W2008591793, https://openalex.org/W2533214323, https://openalex.org/W1934600457, https://openalex.org/W2774335207, https://openalex.org/W2065883524, https://openalex.org/W2076834588, https://openalex.org/W2808443520, https://openalex.org/W2059622452, https://openalex.org/W2598457882, https://openalex.org/W2765854388, https://openalex.org/W2768955070, https://openalex.org/W2761196163, https://openalex.org/W2157709655, https://openalex.org/W2622826443, https://openalex.org/W607748843, https://openalex.org/W2492957203, https://openalex.org/W2964262608, https://openalex.org/W2129438083, https://openalex.org/W2141332006, https://openalex.org/W2057854043, https://openalex.org/W1495971627 |
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