Update README.md

Author: christianrickert

README.md

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 The CU-IScore macro implements two scoring methods applicable for immunofluorescence or DAB/hematoxylin multi-channel images: In short, the novel method returns higher score values for immunofluorescence images with higher average pixel values, while the classic method returns higher score values for DAB/hematoxylin images with lower average pixel values. The classic method is based on the [IHC Profiler](https://doi.org/10.1371/journal.pone.0096801) design, but extends its applicability to multi-channel images with various image formats, bit depths, or pixel value ranges. In addition, CU-IScore creates detailed scoring reports for individual channels as well as a summary table for image batches.
 
 ![histo](https://user-images.githubusercontent.com/19319377/116958138-d4114a80-ac56-11eb-896b-89e4d8bb0a12.png)
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 **Figure 1: Histogram example.** Distribution of pixel counts as a function of pixel values from the grayscale image (top). The histogram is partitioned into four equally-sized intervals for the I-Score calculation. Pixels with values below a certain threshold (black triangle, bottom) are disregarded as background (white peak, left). Pixels within the user-specified value range contribute to the I-Score weighted by three pixel intensity categories (black distribution, center). In addition, pixels with values above a certain threshold (white triangle, bottom) can be disregarded as outliers (white line, right).
 
 ### Software documentation