Fig. 2: Spectral characterization of different brain tissue and tumour types.
From: Hyperspectral imaging benchmark based on machine learning for intraoperative brain tumour detection
Mean (solid lines) and standard deviation (std) (dashed lines) of the entire labelled dataset after applying a basic pre-processing (calibration, extreme band noise removal, and noise filtering) and separated by classes, including the corresponding p-value (magenta dots) computed for each spectral channel using the paired two-sided Wilcoxon Rank Sum test at 5% of significance level between the two compared classes. a TT vs. NT class. b TT vs. BV class. c Primary vs. secondary tumours. d HG vs. LG primary tumours. e G1 vs. G2 primary tumours. f G3 vs. G4 primary tumours.
