Dominguez Mantes Albert, Herrera Antonio, Khven Irina, Schlaeppi Anjalie, Kyriacou Eftychia, Tsissios Georgios, Skoufa Evangelia, Santangeli Luca, Buglakova Elena, Durmus Emine Berna, Manley Suliana, Kreshuk Anna, Arendt Detlev, Aztekin Can, Lingner Joachim, La Manno Gioele, Weigert Martin
Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Nat Methods. 2025 Jun 6. doi: 10.1038/s41592-025-02662-x.
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 .
在大型、有噪声的显微镜图像中识别点状结构是许多生命科学应用中的关键步骤。特别是基于成像的空间转录组学（iST），依赖于在低信噪比图像中精确检测数百万个转录本。尽管计算机视觉最近取得了进展，但目前大多数使用的斑点检测技术仍基于经典信号处理，并且每个数据集都需要繁琐的手动调整。在这里，我们介绍了Spotiflow，一种用于亚像素精确斑点检测的深度学习方法，它将斑点检测表述为多尺度热图和立体视觉流回归问题。Spotiflow支持2D和3D图像，能在不同成像条件下通用，并且比现有方法更节省时间和内存。我们通过对不同数据集进行广泛的定量实验展示了Spotiflow的有效性，并证明其提高的准确性能从iST和实时成像实验中获得的生物学见解带来有意义的改进。Spotiflow作为一个易于使用的Python库以及一个napari插件，可在https://github.com/weigertlab/spotiflow上获取。
