Description of methods used for collection/generation of data:

Datasets were previously published and were collected as described in https://doi.org/10.1117/1.JBO.26.10.106002 and https://doi.org/10.1002/jbio.202100078).

The folder “Datasets” contains curated spectral datasets used based on previous clinical trials for Oesophageal and Colon tissues these are read by the respective Python notebooks

The folder “Optimization” includes the Python notebooks used to generate the optimal filter arrays

Resulting variables saved to file: [classification method]_[tissue type]¬_varibles.npz ( eg. “kNN_Ose_variables.npz”)

The saved variables include: for each number of bands N ‘bands_[N]' centre wavelengths of the selected bands (nM) 'bws_[N]' FWHM of bandwidths of the selected bands (nM) ' pattern_[N]' optimal arrangement of selected bands ' accu_[N]' spectral classification accuracy for optimal bands 'spatial_acc_[N]' spatial classification accuracy for optimal bands 'labels_pred_[N]' classification labels

These variables were condensed in “Band Optimization Summary 23 July 23.xlsx” for easier interpretation

“Band Optimization Summary 23 July 23.xlsx” is a summary of the optimized filters

“Summary.ipynb” plots the figures used in the paper and SI

All information is summarised in the readme.doc file.