ArticleBiomedical journal2022
A review for cell and particle tracking on microscopy images using algorithms and deep learning technologies.
Article in Biomedical journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- Time-lapse image analysis reveals trigger-dependent differences in ASC speck lifetime in the NLRP3 inflammasome.Scientific reports · 2026Article
- Article
- Tui: A Multigenerational and Expert-Correctable Tracker for Cellular Dynamics.Computational and structural biotechnology journal · 2026Article
- Contrastive learning for cell division detection and tracking in live cell imaging data.BMC bioinformatics · 2025Article
- Physics-Inspired Single-Particle Tracking Accelerated with Parallelism.bioRxiv : the preprint server for biology · 2025Article
- In Situ Monitoring and Estimation of α-Lactose Monohydrate Crystal Growth in the Microdroplets.ACS omega · 2025Article
- Enhancing fluorescence correlation spectroscopy with machine learning to infer anomalous molecular motion.Biophysical journal · 2025Article
- A concise guide to fluorescent cell cycle reporters for live-cell imaging.Frontiers in cell and developmental biology · 2025Review
- Effect of shear rate on earlyBiofilm · 2024Article
- Evaluation of particle tracking codes for dispersing particles in porous media.Scientific reports · 2024Article
- BNP-Track: a framework for superresolved tracking.Nature methods · 2024Article
- BNP-Track: A framework for multi-particle superresolved tracking.bioRxiv : the preprint server for biology · 2023Article
- Deep Learning in Diverse Intelligent Sensor Based Systems.Sensors (Basel, Switzerland) · 2022Review
- A finger in every pie - The versatility of chemokines.Biomedical journal · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Time-lapse microscopy images generated by biological experiments have been widely used for observing target activities, such as the motion trajectories and survival states. Based on these observations, biologists can conclude experimental results or present new hypotheses for several biological applications, i.e. virus research or drug design. Many methods or tools have been proposed in the past to observe cell and particle activities, which are defined as single cell tracking and single particle tracking problems, by using algorithms and deep learning technologies. In this article, a review for these works is presented in order to summarize the past methods and research topics at first, then points out the problems raised by these works, and finally proposes future research directions. The contributions of this article will help researchers to understand past development trends and further propose innovative technologies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.