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Table 3 Results of nodule classification at wavelet first decomposition level

From: Automated system for lung nodules classification based on wavelet feature descriptor and support vector machine

Base Angle Sub-band Features Specificity Sensitivity Preciseness
Db1 LH Autc-Clsh 82.60% 63.63% 73.33%
Db2 LH Clsh-IMC2 86.95% 45.45% 66.66%
Db4 HH Autc-Diss 60.86% 95.45% 77.77%
Db1 45° LH Autc-Clsh 86.95% 59.09% 73.33%
Db2 45° LH Autc-IMC2 69.56% 68.18% 68.88%
Db4 45° LH Autc-IMC2 69.56% 90.90% 80%
Db1 90° LH Clpr-Clsh 73.91% 90.90% 82.22%
Db2 90° LH Clpr-Svar 82.60% 59.09% 71.11%
Db4 90° HH Autc-Diffv 52.17% 100% 75.55%
Db1 135° LH Clpr-Sent 86.95% 72.72% 80%
Db2 135° LH Clsh-Diffe 86.95% 72.72% 80%
Db4 135° HH Autc-Cont 65.21% 90.90% 77.77%
  1. The bold data represent the best value obtained.