KnotResolver: Tracking self-intersecting filaments in microscopy using directed graphs
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arXiv
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866913989367169024 |
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| author | Khatri, Dhruv Yadav, Shivani A. Athale, Chaitanya A. |
| author_facet | Khatri, Dhruv Yadav, Shivani A. Athale, Chaitanya A. |
| contents | Quantification of microscopy time-series of in vitro reconstituted motor driven microtubule (MT) transport in 'gliding assays' is typically performed using computational object tracking tools. However, these are limited to non-intersecting and rod-like filaments. Here, we describe a novel computational image-analysis pipeline, KnotResolver, to track image time-series of highly curved self-intersecting looped filaments (knots) by resolving cross-overs. The code integrates filament segmentation and cross-over or 'knot' identification based on directed graph representation, where nodes represent cross-overs and edges represent the path connecting them. The graphs are mapped back to contours and the distance to a reference minimized. We demonstrate the utility of the tool by segmentation and tracking MTs from experiments with dynein-driven wave like filament looping. The accuracy of contour detection is sub-pixel accuracy, and Dice scores indicate a robustness to noise, better than currently used tools. Thus KnotResolver overcomes multiple limitations of widely used tools in microscopy of cytoskeletal filament-like structures. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_12029 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | KnotResolver: Tracking self-intersecting filaments in microscopy using directed graphs Khatri, Dhruv Yadav, Shivani A. Athale, Chaitanya A. Quantitative Methods Biological Physics Biomolecules Quantification of microscopy time-series of in vitro reconstituted motor driven microtubule (MT) transport in 'gliding assays' is typically performed using computational object tracking tools. However, these are limited to non-intersecting and rod-like filaments. Here, we describe a novel computational image-analysis pipeline, KnotResolver, to track image time-series of highly curved self-intersecting looped filaments (knots) by resolving cross-overs. The code integrates filament segmentation and cross-over or 'knot' identification based on directed graph representation, where nodes represent cross-overs and edges represent the path connecting them. The graphs are mapped back to contours and the distance to a reference minimized. We demonstrate the utility of the tool by segmentation and tracking MTs from experiments with dynein-driven wave like filament looping. The accuracy of contour detection is sub-pixel accuracy, and Dice scores indicate a robustness to noise, better than currently used tools. Thus KnotResolver overcomes multiple limitations of widely used tools in microscopy of cytoskeletal filament-like structures. |
| title | KnotResolver: Tracking self-intersecting filaments in microscopy using directed graphs |
| topic | Quantitative Methods Biological Physics Biomolecules |
| url | https://arxiv.org/abs/2404.12029 |