ArticleNature methods2025
Spotiflow: accurate and efficient spot detection for fluorescence microscopy with deep stereographic flow regression.
Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- The membrane-to-cortex distance regulates mDia1 activity to control cortical mechanics.Nature communications · 2026Article
- Spatial Integration of Protein and Chromosomal States Reveals Early Copy-Number Changes and Genotype-Associated Immune Neighborhoods in Serous Ovarian Cancer Evolution.Cancer discovery · 2026Article
- SpotMAX: A generalist framework for multidimensional automatic spot detection and quantification.Science advances · 2026Article
- Imaging-Based Spatial Transcriptomics: Data Interpretation Methods and Biomedical Applications.Biology · 2026Review
- Brieflow: an integrated computational pipeline for high-throughput analysis of optical pooled screening data.Nature communications · 2026Article
- Article
- Brain-wide mapping reveals temporal and sexually dimorphic opioid actions.Communications biology · 2026Article
- Smart hybrid microscopy for cell-friendly detection of rare events.Nature communications · 2026Article
- Image Analysis Approaches for In Situ Hybridization Technologies.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Unified mass imaging maps the lipidome of vertebrate development.Nature methods · 2025Article
- PunctaFinder: An algorithm for automated spot detection in fluorescence microscopy images.Molecular biology of the cell · 2024Article
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
Identification of spot-like structures in large, noisy microscopy images is a crucial step for many life-science applications. Imaging-based spatial transcriptomics (iST), in particular, relies on the precise detection of millions of transcripts in low signal-to-noise images. Despite recent advances in computer vision, most of the currently used spot detection techniques are still based on classical signal processing and require tedious manual tuning per dataset. Here we introduce Spotiflow, a deep learning method for subpixel-accurate spot detection that formulates spot detection as a multiscale heatmap and stereographic flow regression problem. Spotiflow supports 2D and 3D images, generalizes across different imaging conditions and is more time and memory efficient than existing methods. We show the efficacy of Spotiflow by extensive quantitative experiments on diverse datasets and demonstrate that its increased accuracy leads to meaningful improvements in biological insights obtained from iST and live imaging experiments. Spotiflow is available as an easy-to-use Python library as well as a napari plugin at https://github.com/weigertlab/spotiflow .
Indexed as
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40481364What Socratic holds
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 Socratic graph.