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--masks Paths to where masks are stored (Ex: ./segmentation/cellMask.tif) -> If multiple masks are selected the first mask will be used for spatial feature extraction but all will be quantified
--image Path to image(s) for quantification. (Ex: ./registration/*.h5) -> works with .h(df)5 or .tif(f)
--output Path to output directory. (Ex: ./feature_extraction)
--channel_names csv file containing the channel names for the z-stack (Ex: ./my_channels.csv)
--mask_props Space separated list of additional metrics to be calculated for every mask.
This is intended for metrics that depend only on the cell mask. If the metric depends
on signal intensity, use --intensity-props instead.
See list at https://scikit-image.org/docs/dev/api/skimage.measure.html#regionprops
--intensity_props Space separated list of additional metrics to be calculated for every marker separately.
By default only mean intensity is calculated.
If the metric doesn't depend on signal intensity, use --mask-props instead.
See list at https://scikit-image.org/docs/dev/api/skimage.measure.html#regionprops
Currently, the following additional properties can be specified:
--intensity_props gini_index : The Gini index calculates a single number
between 0 and 1, representing how unequal the signal is distributed in each region.
See https://en.wikipedia.org/wiki/Gini_coefficient for more information.
--intensity_props intensity_median : Will calculate the median of intensity values per labeled object in the mask.
--intensity_props intensity_sum : Will calculate the sum of intensity values per labelled object in the mask. This can be useful if you want to count RNA molecules from FISH based images for example.