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Table 1 Geometry features extracted from a MC boundary

From: Microcalcification detection in full-field digital mammograms with PFCM clustering and weighted SVM-based method

Feature index

Feature

Note

GF1

Area of the MC

Number of pixels in the segmented region

GF2

Perimeter of the MC

Number of pixels on the border of the MC

GF3

Compactness

Calculated with \( C=1-\frac{4\pi \times \left(\mathrm{area}\right)}{{\left(\mathrm{perimeter}\right)}^2} \)

GF4

NDM2

Normalized distance-based moments

GF5

NDM3

GF6

NDM4

GF7

Fourier feature

Fourier feature calculated taking boundary pixel as a complex number

GF8

NRL mean

Statistical values from normalized radial length

GF9

NRL standard deviation

GF10

NRL entropy

GF11

NRL area ratio

GF12

RGO mean

Statistical values from relative gradient orientation, measure spiculation, and defined as the acute angle θ between radial direction of a point on the contour and the gradient direction of the point

GF13

RGO standard deviation

GF14

RGO entropy