Fig. 6: Quantitative results at the different stages of the proposed framework and qualitative TMD classification maps in the test set.
From: Hyperspectral imaging benchmark based on machine learning for intraoperative brain tumour detection
a Boxplots of the macro F1-Score of the test set using the eight different classifiers at the three different stages. In the plot, the centre line, the box limits and the whiskers represent the median, the upper and lower quartiles and the 1.5× interquartile range, respectively. Two medians are significantly different at the 5% significance level if their intervals (shaded colour areas) do not overlap. b Average OA, sensitivity, and specificity results of the test set from the 5 folds using the Spatial/Spectral approach (error bars represent the standard deviation). c Examples of SRGB images, GT maps and TMD maps from different tumour types (based on the DNN as supervised algorithm using the optimal hyperparameters).
