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Catheter segmentation in X-ray fluoroscopy using synthetic data and transfer learning with light U-nets
Background and objectivesAutomated segmentation and tracking of surgical instruments and catheters under X-ray fluoroscopy hold the potential for enhanced image guidance in catheter-based endovascular procedures. This article presents a novel method for real-time segmentation of catheters and guidew...
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| 出版年: | Comput Methods Programs Biomed |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Elsevier Scientific Publishers
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7903142/ https://ncbi.nlm.nih.gov/pubmed/32171151 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.cmpb.2020.105420 |
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