The features can be extracted from the images and the objects. Important: Relate nucleoli and parent nucleus.Here, we get rid of the constraints and segment all the nuclei. We also discarded the images touching the borders. However, that mask only included just those objects within a max and a min pixel size. We have partially detected the foreground in the nuclei segmentation in previous steps. To get the background we first select the foreground and subtract it from the original image. The extraction of the background can be useful to measure features that indicate that the images are artefacts. The combination of both masks gives an image with the nuclei in blue and the nucleoli in magenta. Combined mask: nuclei + nucleoli Figure 3: Nuclei and nucleoli masks combined in which the nuclei are in blue and nucleoli in magenta. It will be useful for visual exploration that the masks of the nuclei and nucleoli are saved together into one segmentation mask. This is to avoid the detection of wrong objects outside the cell.Īt this step, the segmentation of the nucleoli can be performed. The segmentation of the dark holes will take place only when the dark holes fall inside a nucleus. To identify the nucleoli the first step is to enhance the dark holes so that they can be segmented. Resulting image after the first logical step of the workflow in which the nuclei were segmented and labelled. Segmentation and labelling of the nuclei Figure 2: Identified nuclei with labels This can be useful later for a proper interpretation of the data analysis. Label and save labelled nuclei: adds the id of each nucleus on top of it.Segmentation mask complete nuclei: gathers all the nuclei identified in the previous step in one mask.Segment complete nuclei: this tool identifies the nuclei within a certain size and excludes those cells that are touching the borders of the image.Background detection: Detection of the foreground and subtraction from the image.Įvery CellProfiler pipeline needs to start by processing the metadata with the tool “Starting modules”.Feature extraction: the order of the tools does not affect the outcome.Segmentation of the nucleoli: since there is no staining for the nucleoli, the holes need to be detected and segmented.Feature extraction of the images and objectsįigure 1: High-level view of the workflow.Segmentation of the nucleoli that fall inside the nuclei.You can also bring your images by uploading the DNA channel of your images to your Galaxy history. That URL contains the image ids that will be downloaded. The images will then show up at the bottom (2) where they need to be selected once again and then copy the URL from the link icon on the top left (3).
In the IDR the images can be selected in the user interface (1). The data can be downloaded from the Image Data Resource ( IDR).In the DNA channel, the nucleoli is shown as the absence of DNA (red arrows). Functions: ribosome biogenesis and cell cycle regulation.Membrane-less organelle in the nucleus of the cell.
Last_modification Last modification: Jul 10, 2021
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