Cell Tracking in C. elegans with Cell Position Heatmap-Based Alignment and Pairwise Detection
Not on the map. Why?
Abstract (arXiv)
3D cell tracking in a living organism has a crucial role in live cell image analysis. Cell tracking in C. elegans has two difficulties. First, cell migration in a consecutive frame is large since they move their head during scanning. Second, cell detection is often inconsistent in consecutive frames due to touching cells and low-contrast images, and these inconsistent detections affect the tracking performance worse. In this paper, we propose a cell tracking method to address these issues, which has two main contributions. First, we introduce cell position heatmap-based non-rigid alignment with test-time fine-tuning, which can warp the detected points to near the positions at the next frame. Second, we propose a pairwise detection method, which uses the information of detection results at the previous frame for detecting cells at the current frame. The experimental results demonstrate the effectiveness of each module, and the proposed method achieved the best performance in comparison.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 18 references that are in the map. First posted on arXiv 20 Mar 2024.
Builds on
6 of 18 references.
References · 6
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
- 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,292
- 2019Weakly Supervised Cell Instance Segmentation by Propagating from Detection Responsecited by 17
- 2020MPM: Joint Representation of Motion and Position Map for Cell Trackingcited by 13
- 2019Joint Multi-frame Detection and Segmentation for Multi-cell Trackingcited by 5
- 2022A Semi-automatic Cell Tracking Process Towards Completing the 4D Atlas of C. elegans Developmentcited by 1
Built on by
Not cited yet.