Cover Image

Spotiflow: accurate and efficient spot detection for fluorescence microscopy with deep stereographic flow regression

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Dominguez Mantes, Albert (Author) , Herrera, Antonio (Author) , Khven, Irina (Author) , Schlaeppi, Anjalie (Author) , Kyriacou, Eftychia (Author) , Tsissios, Georgios (Author) , Skoufa, Evangelia (Author) , Santangeli, Luca (Author) , Buglakova, Elena (Author) , Durmus, Emine Berna (Author) , Manley, Suliana (Author) , Kreshuk, Anna (Author) , Arendt, Detlev (Author) , Aztekin, Can (Author) , Lingner, Joachim (Author) , La Manno, Gioele (Author) , Weigert, Martin (Author)
Format: Article (Journal)
Language:English
Published: 06 June 2025
In: Nature methods
Year: 2025, Volume: 22, Issue: 7, Pages: 1495-1504
ISSN:1548-7105
DOI:10.1038/s41592-025-02662-x
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1038/s41592-025-02662-x
Verlag, lizenzpflichtig, Volltext: https://www.nature.com/articles/s41592-025-02662-x
Get full text
Author Notes:Albert Dominguez Mantes, Antonio Herrera, Irina Khven, Anjalie Schlaeppi, Eftychia Kyriacou, Georgios Tsissios, Evangelia Skoufa, Luca Santangeli, Elena Buglakova, Emine Berna Durmus, Suliana Manley, Anna Kreshuk, Detlev Arendt, Can Aztekin, Joachim Lingner, Gioele La Manno & Martin Weigert
Description
Summary: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.
Item Description:Gesehen am 17.09.2025
Physical Description:Online Resource
ISSN:1548-7105
DOI:10.1038/s41592-025-02662-x

Similar Items