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Table 2 Performance on the testing set obtained by the single classifier

From: Breast DCE-MRI: lesion classification using dynamic and morphological features by means of a multiple classifier system

Feature Formula
Morphological Area, A k n k dxdy where n k is number of voxels in the kth slice of the ROI, d x and d y represent size of voxels
Perimeter length, P k b k where b k is number of boundary voxels in the kth slice of the ROI
Compactness in 3D, COMP \( \frac{S^2}{V_{3 D}} \) where S is the surface and V is the volume, defined as follows: \( s = {\displaystyle \sum_x}{\displaystyle \sum_y}{\displaystyle \sum_z}{b}_{ROI}\left( x, y, z\right){v}_{size} slic{e}_{th} \) where v size is the voxel size, slice th is the slice thickness; and V = n ROI dxdydz where n ROI is total number of voxels in the ROI
Eccentricity, ECC \( \frac{\sqrt{a^2-{b}^2}}{a} \) where a is the major axle shaft and b is the lower one
Dynamic Basal signal, BS Signal intensity before contrast injection
Relative enhancement, RE(t i ) \( \frac{SI\left({t}_i\right)- BS}{BS} \) where t i is the ith temporal instant
Sum of local differences, SOD \( SO{D}_p= Pr{e}_p+{\displaystyle \sum_{i=1}^T}\left| P o s{t}_p(i)- P o s{t}_p\left( i-1\right)\right| \)
  1. ROI region of interest