ArticleMolecular biology of the cell2021
Open-source deep-learning software for bioimage segmentation.
Article in Molecular biology of the cell, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed, 76 citations in OpenAlex.
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- A comparison of super-resolution microscopy techniques for imaging tightly packed microcolonies of an obligate intracellular bacterium.Journal of microscopy · 2026Article
- Automated Intelligent Microscopy for Phenotype Identification, Spatial Localization, and Retargeting of Cells.Methods in molecular biology (Clifton, N.J.) · 2026Article
- The CPEB ortholog Orb2 regulates brain size through the TRIM-NHL RNA-binding protein, Brain tumor.bioRxiv : the preprint server for biology · 2025Article
- OmniSegger: A time-lapse image analysis pipeline for bacterial cells.PLoS computational biology · 2025Article
- Microscopy methods for the in vivo study of nanoscale nuclear organization.Biochemical Society transactions · 2025Review
- Article
- Mitochondrial segmentation and function prediction in live-cell images with deep learning.Nature communications · 2025Article
- Clinical Performance of Cas13a-based Point-of-Care Lateral Flow Assay for DetectingmedRxiv : the preprint server for health sciences · 2024Article
- Defining the boundaries: challenges and advances in identifying cells in microscopy images.Current opinion in biotechnology · 2024Review
- Live-cell imaging in the deep learning era.Current opinion in cell biology · 2023Review
- Artifact Augmentation for Enhanced Tissue Detection in Microscope Scanner Systems.Sensors (Basel, Switzerland) · 2023Article
- Recent Advances in High-Content Imaging and Analysis in iPSC-Based Modelling of Neurodegenerative Diseases.International journal of molecular sciences · 2023Review
- NISNet3D: three-dimensional nuclear synthesis and instance segmentation for fluorescence microscopy images.Scientific reports · 2023Article
- A biologist's guide to planning and performing quantitative bioimaging experiments.PLoS biology · 2023Article
- Deep learning-enabled segmentation of ambiguous bioimages with deepflash2.Nature communications · 2023Article
- Different approaches to Imaging Mass Cytometry data analysis.Bioinformatics advances · 2023Review
- Image analysis workflows to reveal the spatial organization of cell nuclei and chromosomes.Nucleus (Austin, Tex.) · 2022Article
- Unravelling cell migration: defining movement from the cell surface.Cell adhesion & migration · 2022Review
- Cellpose 2.0: how to train your own model.Nature methods · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Microscopy images are rich in information about the dynamic relationships among biological structures. However, extracting this complex information can be challenging, especially when biological structures are closely packed, distinguished by texture rather than intensity, and/or low intensity relative to the background. By learning from large amounts of annotated data, deep learning can accomplish several previously intractable bioimage analysis tasks. Until the past few years, however, most deep-learning workflows required significant computational expertise to be applied. Here, we survey several new open-source software tools that aim to make deep-learning-based image segmentation accessible to biologists with limited computational experience. These tools take many different forms, such as web apps, plug-ins for existing imaging analysis software, and preconfigured interactive notebooks and pipelines. In addition to surveying these tools, we overview several challenges that remain in the field. We hope to expand awareness of the powerful deep-learning tools available to biologists for image analysis.
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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.