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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2306.06960 |
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| _version_ | 1866917612338806784 |
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| author | Kelner, Ori Weinstein, Or Rivlin, Ehud Goldenberg, Roman |
| author_facet | Kelner, Ori Weinstein, Or Rivlin, Ehud Goldenberg, Roman |
| contents | Following the successful debut of polyp detection and characterization, more advanced automation tools are being developed for colonoscopy. The new automation tasks, such as quality metrics or report generation, require understanding of the procedure flow that includes activities, events, anatomical landmarks, etc. In this work we present a method for automatic semantic parsing of colonoscopy videos. The method uses a novel DL multi-label temporal segmentation model trained in supervised and unsupervised regimes. We evaluate the accuracy of the method on a test set of over 300 annotated colonoscopy videos, and use ablation to explore the relative importance of various method's components. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_06960 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Semantic Parsing of Colonoscopy Videos with Multi-Label Temporal Networks Kelner, Ori Weinstein, Or Rivlin, Ehud Goldenberg, Roman Computer Vision and Pattern Recognition Following the successful debut of polyp detection and characterization, more advanced automation tools are being developed for colonoscopy. The new automation tasks, such as quality metrics or report generation, require understanding of the procedure flow that includes activities, events, anatomical landmarks, etc. In this work we present a method for automatic semantic parsing of colonoscopy videos. The method uses a novel DL multi-label temporal segmentation model trained in supervised and unsupervised regimes. We evaluate the accuracy of the method on a test set of over 300 annotated colonoscopy videos, and use ablation to explore the relative importance of various method's components. |
| title | Semantic Parsing of Colonoscopy Videos with Multi-Label Temporal Networks |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2306.06960 |