.png){kind=icon}
.png){kind=icon}
Return
Network Flow Method Integrates Skeleton Information for Multiple C. elegans Tracking
.png){kind=icon}
OA
AI
DOI：10.3390/s25030603.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In order to solve the issues arising from collisions, this paper proposes a network flow method combined with skeleton information for multiple C. elegans tracking. In the intra-track stage, non-colliding C. elegans are identified and associated as trajectory fragments based on their motion and positional information, and colliding C. elegans are then segmented based on an improved skeleton algorithm and matched as trajectory fragments. Subsequently, the trajectory fragments are employed as vertices to construct a network flow model. The minimum-cost method is then utilized to solve the model, thereby obtaining the optimal solution for the multiple C. elegans trajectories. The proposed method was evaluated using video data of the C. elegans population at three distinct ages: L4, young adult, and D1. The experimental results demonstrate that the method proposed in this paper exhibits a MOTA between 0.86 and 0.92, and an MOTP between 0.78 and 0.83, which indicates that the proposed method can be employed in multiple C. elegans tracking. It is our hope that this method will prove beneficial to C. elegans laboratories, offering a novel approach to multiple C. elegans tracking.
Keywords:
multiple C. elegans tracking
network flow method
skeleton algorithm
adjacent frame match
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.5
Papers:
7.1W
Citations:
20.9W