Watershed:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] RemoveHoles:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] Two-class or three-class thresholding?:Two classesĪssign pixels in the middle intensity class to the foreground or the background?:Foreground Select the measurement to threshold with:None Lower and upper bounds on threshold:0.0,1.0 Threshold:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] MedianFilter:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] Select the image with the desired dimensions:None ![]() Resizing method:Resize by a fraction or multiple of the original size Resize:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] Select image to match in maximum intensity:None Intensity range for the output image:0.0,1.0 Intensity range for the input image:0.0,1.0 Upper intensity limit for the input image:1.0 Lower intensity limit for the input image:0.0 Method to calculate the maximum intensity:Custom Method to calculate the minimum intensity:Custom Rescaling method:Stretch each image to use the full intensity range RescaleIntensity:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] Groups:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] ![]() Select the rule criteria:and (metadata does ChannelNumber "0") Select the rule criteria:and (metadata does ChannelNumber "1") Select the rule criteria:and (metadata does ChannelNumber "2") NamesAndTypes:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] Select the filtering criteria:and (file does contain "") Regular expression to extract from folder name:(?P)$ Regular expression to extract from file name:^(?P.*)_xy(?P)_ch(?P) Metadata extraction method:Extract from file/folder names Metadata:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] Select the rule criteria:and (extension does isimage) (directory doesnot containregexp "\.") tiff format representing the downscaled pixel probabilities after Ilastik pixel classification.Images:|batch_state:array(, dtype=uint8)|enabled:True|wants_pause:False] analysis/cpout/probabilities: contains 3 channel images in 16-bit.Segmentation masks are single-channel images that match the input images in size, with non-zero grayscale values indicating the IDs of segmented objects. analysis/cpout/masks: contains single-channel segmentation masks in 16-bit.tiff images to the analysis/cpout/probabilities folder.Īfter image segmentation the following files have been generated: The downscaled pixel probability images are written out as 16-bit, 3 channel.tiff images to the analysis/cpout/masks folder. The segmentation masks are written out as 16-bit, single-channel.The segmentation masks are converted to 16-bit images.The IdentifySecondaryObjects module expands from the identified nuclei to the border of the full cell probability generated in step 3 or until touching the neighboring cell.The MeasureObjectSizeShape module measures the size of the nuclei and the FilterObjects module filters nuclei below a specified threshold.The advanced settings can be adjusted to improve segmentation. Use the test mode and enable the "eye" icon next to the module to observe if nuclei are correctly segmented. The IdentifyPrimaryObjects module is crucial to correctly identifying nuclei.This step can be adjusted or removed to increase segmentation success. The nuclear probabilities are smoothed using a gaussian filter. ![]() The nulcear and cytoplasmic channels are summed up to form a single channel indicating the full cell probability.In ColorToGray the 3 channel probability images are split into their individual channels: channel 1 - nucleus channel 2 - cytoplasm channel 3 - background.The images containing pixel probabilities are downscaled by a factor of 0.5 to match the initial image dimensions.The files ending with _Probabilities.tiff are read in as part of the NamesAndTypes module.The following steps are part of the pipeline: In the Output Settings adjust the Default Output Folder to analysis/cpout.Drag and drop the analysis/ilastik folder into the Images window.Set up the pipeline by importing the resources/pipelines/2_segment_ilastik.cppipe pipeline into CellProfiler and perform following steps: To segment individual objects (here these are cells) in images, the following CellProfiler pipeline reads in pixel probabilities (generated in Ilastik pixel classification) for segmentation.
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