mlsanityData to 7 Oct 2026

EmbedTrack -- Simultaneous Cell Segmentation and Tracking Through Learning Offsets and Clustering Bandwidths

arXiv 2204.10713 ↗First posted 22 Apr 2022cs.CV cs.LGcited by 16

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Abstract (arXiv)

A systematic analysis of the cell behavior requires automated approaches for cell segmentation and tracking. While deep learning has been successfully applied for the task of cell segmentation, there are few approaches for simultaneous cell segmentation and tracking using deep learning. Here, we present EmbedTrack, a single convolutional neural network for simultaneous cell segmentation and tracking which predicts easy to interpret embeddings. As embeddings, offsets of cell pixels to their cell center and bandwidths are learned. We benchmark our approach on nine 2D data sets from the Cell Tracking Challenge, where our approach performs on seven out of nine data sets within the top 3 contestants including three top 1 performances. The source code is publicly available at https://git.scc.kit.edu/kit-loe-ge/embedtrack.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Builds on 14 of its 62 references that are in the map. First posted on arXiv 22 Apr 2022.

Builds on

14 of 62 references.

References · 14

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2019Deep Learning in Video Multi-Object Tracking: A Surveycited by 107
  3. 2019Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidthcited by 88
  4. 2019Spatial-Temporal Relation Networks for Multi-Object Trackingcited by 74
  5. 2019Star-convex Polyhedra for 3D Object Detection and Segmentation in Microscopycited by 45
  6. 2022Graph Neural Network for Cell Tracking in Microscopy Videoscited by 19
  7. 2018Microscopy Cell Segmentation via Convolutional LSTM Networkscited by 17
  8. 2020MPM: Joint Representation of Motion and Position Map for Cell Trackingcited by 13
  9. 2021CellTrack R-CNN: A Novel End-To-End Deep Neural Network for Cell Segmentation and Tracking in Microscopy Imagescited by 10
  10. 2020Weakly-Supervised Cell Tracking via Backward-and-Forward Propagationcited by 8
  11. 2017Cell Tracking via Proposal Generation and Selectioncited by 5
  12. 2021VoxelEmbed: 3D Instance Segmentation and Tracking with Voxel Embedding based Deep Learningcited by 5
2 more
  1. 2015SPF-CellTracker: Tracking multiple cells with strongly-correlated moves using a spatial particle filtercited by 3
  2. 2016Fuzzy-based Propagation of Prior Knowledge to Improve Large-Scale Image Analysis Pipelinescited by 3

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Cited by year

Citing papers per year: 2022: 1; 2023: 6; 2024: 7; 2025: 2.

16 papers.

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  1. 2024Trackastra: Transformer-based cell tracking for live-cell microscopycited by 14
  2. 2023Large-Scale Multi-Hypotheses Cell Tracking Using Ultrametric Contours Mapscited by 7
  3. 2024Tracking one-in-a-million: Large-scale benchmark for microbial single-cell tracking with experiment-aware robustness metricscited by 6
  4. 2023Generative modeling of living cells with SO(3)-equivariant implicit neural representationscited by 4
  5. 2024SynCellFactory: Generative Data Augmentation for Cell Trackingcited by 4
  6. 2023Unsupervised Learning of Object-Centric Embeddings for Cell Instance Segmentation in Microscopy Imagescited by 3
  7. 2024Cell Tracking according to Biological Needs -- Strong Mitosis-aware Multi-Hypothesis Tracker with Aleatoric Uncertaintycited by 3
  8. 2022Cell tracking for live-cell microscopy using an activity-prioritized assignment strategycited by 2
  9. 2023The TYC Dataset for Understanding Instance-Level Semantics and Motions of Cells in Microstructurescited by 2
  10. 2023Cell Tracking-by-detection using Elliptical Bounding Boxescited by 1
  11. 2023DistNet2D: Leveraging long-range temporal information for efficient segmentation and trackingcited by 1
  12. 2025Segment Anything for Cell Trackingcited by 1
4 more
  1. 2024Deep Temporal Sequence Classification and Mathematical Modeling for Cell Tracking in Dense 3D Microscopy Videos of Bacterial Biofilmscited by 0
  2. 2024CHOTA: A Higher Order Accuracy Metric for Cell Trackingcited by 0
  3. 2024Cell as Point: One-Stage Framework for Efficient Cell Trackingcited by 0
  4. 2025Self-Supervised Learning Strategies for a Platform to Test the Toxicity of New Chemicals and Materialscited by 0