sanderthierens
commented
3 years ago At the moment, there are three different methods to do this
- Based on the binned counts, we search the bin in which the n% quantile is located
- For each sample we calculate quantile values and reduces this with a median
- Per partition we group intensities an calculate quantile value followed by a median reduction
To avoid working with very small floats in the feature extraction phase, we want to rescale the pixel values to the [0-1] range. This can be achieved with a simple min-max normalization. Potentially, we can use quantile quantile normalization where instead of min and max we use the 5th and 95th quantile.