# Table 3 Classification performance on Epistroma dataset

Method Perf RP + Magnitude RP Magnitude
SVM DTB SVM DTB SVM DTB
(1): Baseline performance of existing Shearlet-based methods
Vo et al. ACC% $$\underline{96} .\underline{44} \% \pm \underline{1} .\underline{47} \%$$ $$95.42\% \pm 1.03\%$$ $$95.50\% \pm 1.52\%$$ $$94.26\% \pm 1.95\%$$ $$94.48\% \pm 1.54\%$$ $$94.26\% \pm 1.35\%$$
AUC $$\underline{0} .\underline{9895} \pm \underline{0} .\underline{0082}$$ $$0.9897 \pm 0.0047$$ $$0.9873 \pm 0.0078$$ $$0.9839 \pm 0.0087$$ $$0.9830 \pm 0.0083$$ $$0.9763 \pm 0.0102$$
Sen $$\underline{0} .\underline{9685} \pm \underline{0} .\underline{0131}$$ $$0.9443 \pm 0.0162$$ $$0.9685 \pm 0.0117$$ $$0.9467 \pm 0.0268$$ $$0.9588 \pm 0.0182$$ $$0.9564 \pm 0.0152$$
Prec $$\underline{0} .\underline{9722} \pm \underline{0} .\underline{0170}$$ $$0.9787 \pm 0.0083$$ $$0.9577 \pm 0.0260$$ $$0.9576 \pm 0.0220$$ $$0.9501\pm 0.0219$$ $$0.9487 \pm 0.0193$$
Meshkini and Ghassemian ACC% $$\textit{96.08}\% \pm \textit{1.24}\%$$ $$\textit{96.29}\% \pm \textit{1.86}\%$$ $$\textit{95.35}\% \pm \textit{1.37}\%$$ $$\textit{96.37} \% \pm \textit{2.30}\%$$ $$95.35\% \pm 1.49\%$$ $$96.44 \% \pm 2.20\%$$
AUC $$\textit{0.9926} \pm \textit{0.0046}$$ $$\textit{0.9929} \pm \textit{0.0041}$$ $$\textit{0.9887} \pm \textit{0.0058}$$ $$\textit{0.9919} \pm \textit{0.0077}$$ $$0.9899 \pm 0.0050$$ $$0.9908 \pm 0.0068$$
Sen $$\textit{0.9710} \pm \textit{0.0190}$$ $$\textit{0.9600} \pm \textit{0.0222}$$ $$\textit{0.9685} \pm \textit{0.0207}$$ $$\textit{0.9600} \pm \textit{0.0269}$$ $$0.9722 \pm 0.0161$$ $$0.9564 \pm 0.0274$$
Prec $$\textit{0.9642} \pm \textit{0.0169}$$ $$\textit{0.9778} \pm \textit{0.0151}$$ $$\textit{0.9550} \pm \textit{0.0183}$$ $$\textit{0.9791} \pm \textit{0.0184}$$ $$0.9517 \pm 0.0186$$ $$0.9840 \pm 0.0181$$
Zhou et al. ACC% $$\textit{89.68}\% \pm \textit{1.33}\%$$ $$\textit{88.30}\% \pm \textit{2.68}\%$$ $$\textit{81.69}\% \pm \textit{2.53}\%$$ $$\textit{79.65} \% \pm \textit{3.11}\%$$ $$84.45\% \pm 2.98\%$$ $$87.13 \% \pm 2.95\%$$
AUC $$\textit{0.9506} \pm \textit{0.0158}$$ $$\textit{0.9400} \pm \textit{0.0223}$$ $$\textit{0.8748} \pm \textit{0.0222}$$ $$\textit{0.8721} \pm \textit{0.0367}$$ $$0.9110 \pm 0.0194$$ $$0.9416 \pm 0.0244$$
Sen $$\textit{0.9370} \pm \textit{0.0219}$$ $$\textit{0.9103} \pm \textit{0.0287}$$ $$\textit{0.8934} \pm \textit{0.0363}$$ $$\textit{0.8666} \pm \textit{0.0343}$$ $$0.9236 \pm 0.0141$$ $$0.9102 \pm 0.0327$$
Prec $$\textit{0.8961} \pm \textit{0.0183}$$ $$\textit{0.8968} \pm \textit{0.0275}$$ $$\textit{0.8186} \pm \textit{0.0251}$$ $$\textit{0.8088} \pm \textit{0.0301}$$ $$0.8357 \pm 0.0330$$ $$0.8799 \pm 0.0282$$
Dong et al. ACC% $$\textit{95.72}\% \pm \textit{1.54}\%$$ $$\textit{95.28}\% \pm \textit{1.66}\%$$ $$\textit{94.84}\% \pm \textit{1.59}\%$$ $$\textit{93.39}\% \pm \textit{2.11}\%$$ $$95.86\% \pm 1.32\%$$ $$93.75\% \pm 1.15\%$$
AUC $$\textit{0.9882} \pm \textit{0.0071}$$ $$\textit{0.9837} \pm \textit{0.0089}$$ $$\textit{0.9836} \pm \textit{0.0071}$$ $$\textit{0.9776} \pm \textit{0.0132}$$ $$0.9884 \pm 0.0082$$ $$0.9836 \pm 0.0101$$
Sen $$\textit{0.9551} \pm \textit{0.0162}$$ $$\textit{0.9503} \pm \textit{0.0271}$$ $$\textit{0.9503} \pm \textit{0.0218}$$ $$\textit{0.9187} \pm \textit{0.0300}$$ $$0.9685 \pm 0.0103$$ $$0.9600 \pm 0.0182$$
Prec $$\textit{0.9735} \pm \textit{0.0227}$$ $$\textit{0.9707} \pm \textit{0.0178}$$ $$\textit{0.9637} \pm \textit{0.0211}$$ $$\textit{0.9697} \pm \textit{0.0201}$$ $$0.9630 \pm 0.0194$$ $$0.9381 \pm 0.0231$$
(2): Proposed Shearlet-Based Methods For Textured Bio-medical Image Classification
CM ACC% $$\underline{97} .\underline{24} \% \pm \underline{1} .\underline{27} \%$$ $$94.41\% \pm 1.48\%$$ $$96.66\% \pm 1.14\%$$ $$94.99\% \pm 1.43\%$$ $$96.00\% \pm 1.30\%$$ $$94.19\% \pm 2.19\%$$
AUC $$\underline{0} .\underline{9917} \pm \underline{0} .\underline{0067}$$ $$0.9819 \pm 0.0126$$ $$0.9925 \pm 0.0064$$ $$0.9828 \pm 0.0116$$ $$0.9863 \pm 0.0087$$ $$0.9828 \pm 0.0091$$
Sen $$\underline{0} .\underline{9733} \pm \underline{0} .\underline{0126}$$ $$0.9419 \pm 0.0258$$ $$0.9672 \pm 0.0129$$ $$0.9503 \pm 0.0134$$ $$0.9636 \pm 0.0163$$ $$0.9418 \pm 0.0294$$
Prec $$\underline{0} .\underline{9807} \pm \underline{0} .\underline{0150}$$ $$0.9646 \pm 0.0202$$ $$0.9769 \pm 0.0130$$ $$0.9658 \pm 0.0175$$ $$0.9696 \pm 0.0116$$ $$0.9607 \pm 0.0186$$
LBP ACC% $$95.64\% \pm 1.32\%$$ $$95.57\% \pm 2.04\%$$ $$95.50\% \pm 1.06\%$$ $$94.04\% \pm 1.56\%$$ $$95.71\% \pm 1.39\%$$ $$93.90\% \pm 1.75\%$$
AUC $$0.9890 \pm 0.0073$$ $$0.9905 \pm 0.0069$$ $$0.9871 \pm 0.0076$$ $$0.9850 \pm 0.0054$$ $$0.9876 \pm 0.0088$$ $$0.9800 \pm 0.0113$$
Sen $$0.9624 \pm 0.0146$$ $$0.9479 \pm 0.0261$$ $$0.9661 \pm 0.0178$$ $$0.9394 \pm 0.0221$$ $$0.9600 \pm 0.0153$$ $$0.9406 \pm 0.0239$$
Prec $$0.9653 \pm 0.0203$$ $$0.9779 \pm 0.0210$$ $$0.9594 \pm 0.0133$$ $$0.9607 \pm 0.0176$$ $$0.9687 \pm 0.0206$$ $$0.9573 \pm 0.0194$$
LOSIB ACC% $$96.29\% \pm 1.47\%$$ $$95.13\% \pm 1.61\%$$ $$95.50\% \pm 1.32\%$$ $$96.65\% \pm 1.51\%$$ $$95.35\% \pm 1.85\%$$ $$93.10\% \pm 1.29\%$$
AUC $$0.9900 \pm 0.0069$$ $$0.9870 \pm 0.0074$$ $$0.9868 \pm 0.0073$$ $$0.9911 \pm 0.0065$$ $$0.9892 \pm 0.0087$$ $$0.9825 \pm 0.0103$$
Sen $$0.9733 \pm 0.0096$$ $$0.9454 \pm 0.0245$$ $$0.9721 \pm 0.0152$$ $$0.9624 \pm 0.0218$$ $$0.9758 \pm 0.0141$$ $$0.9503 \pm 0.0276$$
Prec $$0.9656 \pm 0.0215$$ $$0.9729 \pm 0.0179$$ $$0.9541 \pm 0.0203$$ $$0.9816 \pm 0.0132$$ $$0.9487 \pm 0.0239$$ $$0.9362 \pm 0.0194$$
SFTA ACC% $$95.71\% \pm 1.54\%$$ $$93.90\% \pm 1.81\%$$ $$95.28\% \pm 2.16\%$$ $$91.57\% \pm 1.91\%$$ $$94.33\% \pm 1.52\%$$ $$92.01 \% \pm 2.07\%$$
AUC $$0.9881 \pm 0.0064$$ $$0.9841 \pm 0.0106$$ $$0.9870 \pm 0.0068$$ $$0.9775 \pm 0.0093$$ $$0.9824 \pm 0.0080$$ $$0.9732 \pm 0.0125$$
Sen $$0.9661 \pm 0.0137$$ $$0.9297 \pm 0.0282$$ $$0.9624 \pm 0.0145$$ $$0.9006 \pm 0.0265$$ $$0.9636 \pm 0.0114$$ $$0.9455 \pm 0.0221$$
Prec $$0.9628 \pm 0.0169$$ $$0.9676 \pm 0.0184$$ $$0.9593 \pm 0.0233$$ $$0.9572 \pm 0.0266$$ $$0.9438 \pm 0.024$$ $$0.9232 \pm 0.0178$$
(3): Integrating Shearlet-based existing techniques with our proposed methods
Fusion #1 ACC% $$96.59\% \pm 1.24\%$$ $$95.93\% \pm 1.95\%$$ $$96.37\% \pm 1.14\%$$ $$94.98\% \pm 0.73\%$$ $$95.71\% \pm 1.25\%$$ $$95.13 \% \pm 1.37\%$$
AUC $$0.9889 \pm 0.0111$$ $$0.9910 \pm 0.0070$$ $$0.9889 \pm 0.0103$$ $$0.9838 \pm 0.0131$$ $$0.9877 \pm 0.0104$$ $$0.9841 \pm 0.0104$$
Sen $$0.9612 \pm 0.0126$$ $$0.9624 \pm 0.0224$$ $$0.9612 \pm 0.0179$$ $$0.9406 \pm 0.0194$$ $$0.9563 \pm 0.0155$$ $$0.9503 \pm 0.0201$$
Prec $$0.9816 \pm 0.0140$$ $$0.9696 \pm 0.0175$$ $$0.9780 \pm 0.0135$$ $$0.9752 \pm 0.0139$$ $$0.9721 \pm 0.0185$$ $$0.9682 \pm 0.0172$$
Fusion #2 ACC% $$97.09\% \pm 1.49\%$$ $$94.98\% \pm 1.56\%$$ $$96.37\% \pm 1.45\%$$ $$95.86\% \pm 2.11\%$$ $$96.73\% \pm 1.33\%$$ $$95.28 \% \pm 1.54\%$$
AUC $$0.9910 \pm 0.0099$$ $$0.9829 \pm 0.0111$$ $$0.9908 \pm 0.0092$$ $$0.9884 \pm 0.0113$$ $$0.9892 \pm 0.0097$$ $$0.9872 \pm 0.0106$$
Sen $$0.9660 \pm 0.0205$$ $$0.9382 \pm 0.0211$$ $$0.9600 \pm 0.0182$$ $$0.9527 \pm 0.0271$$ $$0.9685 \pm 0.0192$$ $$0.9612 \pm 0.0124$$
Prec $$0.9853 \pm 0.0111$$ $$0.9778 \pm 0.0213$$ $$0.9791 \pm 0.0128$$ $$0.9779 \pm 0.0201$$ $$0.9771 \pm 0.0158$$ $$0.9607 \pm 0.0250$$
Fusion #3 ACC% $$\underline{97} .\underline{46} \% \pm \underline{1} .\underline{24} \%$$ $$96.22\% \pm 1.60\%$$ - - - -
AUC $$\underline{0} .\underline{9925} \pm \underline{0} .\underline{0093}$$ $$0.9920 \pm 0.0047$$ - - - -
Sen $$\underline{0} .\underline{9769} \pm \underline{0} .\underline{0156}$$ $$0.9551 \pm 0.0229$$ - - - -
Prec $$\underline{0} .\underline{9809} \pm \underline{0} .\underline{0165}$$ $$0.9814 \pm 0.0103$$ - - - -
1. The results shown in italic are of experiments that are not explored in the original research papers
2. The underlined classification results represent the highest results for each corresponding section