Scalable Cytometry Image Processing (SCIP) is an open-source tool that implements an image processing pipeline on top of Dask, a distributed computing framework written in Python. SCIP performs projection, illumination correction, image segmentation and masking, and feature extraction.
To be able to handle CZI images we can load them using aicsimageio. The CZI images contain 'scenes', each scene corresponds to a treatment. The scenes have dimensions MTCZXY equal to (56, 1, 6, 3, 1000, 1000). The user specifices which scene to process for each run through a command line argument or config entry.
The planes are stored as tiles. Each tile contains many cells which we want to identify through segmentation. The aicsimageio provides access to image data as a Dask Array.
To be able to handle CZI images we can load them using
aicsimageio. The CZI images contain 'scenes', each scene corresponds to a treatment. The scenes have dimensions MTCZXY equal to (56, 1, 6, 3, 1000, 1000). The user specifices which scene to process for each run through a command line argument or config entry.The planes are stored as tiles. Each tile contains many cells which we want to identify through segmentation. The
aicsimageioprovides access to image data as a Dask Array.