Summary We present the "spatial transcriptomics imaging framework" (STIM), an imaging-based computational framework focused on visualizing and aligning high-throughput spatial sequencing datasets. STIM is built
但是这种分割方法也存在问题,那就是对于拿着不规则的细胞,比如神经细胞、肌肉细胞等划分的还是不精确,这一点的得到了上海10X技术人员的确认。 另外一个比较好的细胞分割技术是SCS,文章在SCS: cell segmentation for high-resolution spatial transcriptomics(nature methods)。该方法利用深度学习和图像处理技术,从高分辨率...
另外一个比较好的细胞分割技术是SCS,文章在SCS: cell segmentation for high-resolution spatial transcriptomics(nature methods)。该方法利用深度学习和图像处理技术,从高分辨率空间转录组图像中分割出单个细胞,并为每个细胞分配一个唯一的标识符。SCS不仅可以提高细胞分割的准确性和效率,而且可以为后续的空间转录组数据挖...
Computer vision for image-based transcriptomics. Methods 85, 44–53 (2015). Article CAS PubMed Google Scholar Sommer, C., Straehle, C., Köthe, U. & Hamprecht, F.A. Ilastik: interactive learning and segmentation toolkit. in 2011 IEEE International Symposium on Biomedical Imaging: From ...
indexed-4.0.0. The Slide-Seq data are available from the publicly archived data by Stickels et al.1. Specifically, we used the Puck_200115_08 data fromhttps://singlecell.broadinstitute.org/single_cell/study/SCP815/highly-sensitive-spatial-transcriptomics-at-near-cellular-resolution-with-slide-...
Computer vision for image-based transcriptomics. Methods 85, 44–53 (2015). Article CAS PubMed Google Scholar Sommer, C., Straehle, C., Köthe, U. & Hamprecht, F.A. Ilastik: interactive learning and segmentation toolkit. in 2011 IEEE International Symposium on Biomedical Imaging: From ...
另外一个比较好的细胞分割技术是SCS,文章在SCS: cell segmentation for high-resolution spatial transcriptomics(nature methods)。该方法利用深度学习和图像处理技术,从高分辨率空间转录组图像中分割出单个细胞,并为每个细胞分配一个唯一的标识符。SCS不仅可以提高细胞分割的准确性和效率,而且可以为后续的空间转录组数据挖...
and the spatial distribution of markers through a novel 3D-shell analysis. This analysis is a core feature of our script. The calculation of the shells is not based on simple spherical approximations, but uses the actual distances to the spheroid hull, which leads to more consistent subdivisions...
Tissue Microarrays (TMAs), widely utilized in the field of pathology, have now found a powerful ally in Image-based Spatial Transcriptomics (ST). By analyzing various gene expression data with high resolution, image-based ST data on TMA can provide the heterogeneous patterns of tumor ...
We illustrate STIM's capabilities by representing, interactively visualizing, 3D rendering, automatically registering and segmenting publicly available spatial sequencing data from 13 serial sections of mouse brain tissue by adapting tried-and-tested algorithms....