mlsanityData to 13 Oct 2026

SynCellFactory: Generative Data Augmentation for Cell Tracking

arXiv 2404.16421 ↗First posted 25 Apr 2024cs.CVcited by 4

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Abstract (arXiv)

Cell tracking remains a pivotal yet challenging task in biomedical research. The full potential of deep learning for this purpose is often untapped due to the limited availability of comprehensive and varied training data sets. In this paper, we present SynCellFactory, a generative cell video augmentation. At the heart of SynCellFactory lies the ControlNet architecture, which has been fine-tuned to synthesize cell imagery with photorealistic accuracy in style and motion patterns. This technique enables the creation of synthetic yet realistic cell videos that mirror the complexity of authentic microscopy time-lapses. Our experiments demonstrate that SynCellFactory boosts the performance of well-established deep learning models for cell tracking, particularly when original training data is sparse.

Key facts. Cited by 4 papers in the map (data through 13 Oct 2026). Builds on 21 of its 46 references that are in the map. First posted on arXiv 25 Apr 2024.

Builds on

21 of 46 references.

References · 21

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,950
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  3. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,213
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9 more
  1. 2021Data Augmentation Can Improve Robustnesscited by 193
  2. 2022Fake it till you make it: Learning transferable representations from synthetic ImageNet clonescited by 172
  3. 2023Generative AI for Medical Imaging: extending the MONAI Frameworkcited by 68
  4. 2020Hierarchical Amortized Training for Memory-efficient High Resolution 3D GANcited by 60
  5. 2017A Bayesian Data Augmentation Approach for Learning Deep Modelscited by 50
  6. 2022Can segmentation models be trained with fully synthetically generated data?cited by 37
  7. 2022EmbedTrack -- Simultaneous Cell Segmentation and Tracking Through Learning Offsets and Clustering Bandwidthscited by 16
  8. 2020CellCycleGAN: Spatiotemporal Microscopy Image Synthesis of Cell Populations using Statistical Shape Models and Conditional GANscited by 7
  9. 2021ASIST: Annotation-free Synthetic Instance Segmentation and Tracking by Adversarial Simulationscited by 3

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Cited by year

Citing papers per year: 2024: 1; 2025: 3.

4 papers.

  1. 2025Content Generation Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challengescited by 5
  2. 2025CellStyle: Improved Zero-Shot Cell Segmentation via Style Transfercited by 1
  3. 2025Exploring the Effectiveness of Deep Features from Domain-Specific Foundation Models in Retinal Image Synthesiscited by 1
  4. 2024CHOTA: A Higher Order Accuracy Metric for Cell Trackingcited by 0