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NuanceCellClustering

main_gui.m : manually registration between Nuance and H&E images input:

  1. H&E image 2, multispectral images (raw) output: Overlaid H&E image

main.m: cell clustering based on cos-kmediods clustering Cell intensities are calculated based on the multispectral imaging intensities For a ROI, input:

  1. H&E image (.jpg) 2, multispectral images (preprocessed) (.tif) 3, cell segments position (.zip)

parameters: 1, t: threthold for removing cell outliers 2, k: the number of cell clusters 3, dis: distance measure

output: 1: a cell-biomarker matrix of all ROIs 2, a clustering results of the cell-biomarker matrix 3, the number of cell in each cluster 4, visulization of clustering results: t-SNE, MST, histogram of median intensity per cluster, positions of each cell cluster on all H&E Images 5, the cell count per cluster, per folder(image), and per cluster per folder(image)

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