Spotiflow
A deep learning-based, threshold-agnostic, subpixel-accurate 2D and 3D spot detection method for fluorescence microscopy and spatial transcriptomics.
What is Spotiflow?
Spotiflow is a deep learning-based software tool for detecting spot-like structures in fluorescence microscopy images and 3D volumes with subpixel accuracy. It solves the problem of accurate, automated transcript detection in spatial transcriptomics and general spot detection in bioimaging without requiring manual threshold setting. The method uses stereographic flow regression to precisely localize spots.
Bioimage analysts, computational biologists, and researchers working with fluorescence microscopy data, particularly in spatial transcriptomics (e.g., multiplexed FISH) or any field requiring precise detection of spot-like signals in 2D or 3D.
Developers choose Spotiflow for its combination of subpixel accuracy, threshold-agnostic design, and ease of integration into existing workflows via its CLI, API, and plugins for popular platforms like Napari and QuPath. Its availability of pre-trained models allows for immediate use without extensive training.
Overview
Accurate and efficient spot detection for microscopy data
Use Cases
Best For
- Detecting RNA transcripts in multiplexed fluorescence in situ hybridization (FISH) images for spatial transcriptomics
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