P051116-P1

*In these section we propose an algorithm for the characterization of carcinogenic microcalcifications by morphology descriptor BI-RAD 4. the algorithm is implemented by means of a two-phase algorithm; The first phase is the segmentation of images where suspicious microcalcifications are obtained, and the second phase these objects are classified for diagnosis using morphology descriptors BI-RAD 4.*

*An improved non-linear based filter using enhanced factor for image thresholding algorithm*

**The proposal:**

*Let f(x, y) the source image, and g(x, y) = α output image, where α is the enhanced factor defined by:*

*α ← t / (m – t) (1) α ← m – (v * (1+ α)) (2) α ← α – ( α * t) (3)*

in (1), t is the threshold value that minimizes the weighted within-class variance of f(x,y), m = max( f( x, y ) ) and v = med { f ( xi, yj ), i, j ϵ W }, where W is n X n sub-matrix whit n = 3, Noise, brightness and contrast level are automatic adjusted by (2) and (3) respectively, then each object is labeled.

A propose algorithm for the characterization of carcinogenic microcalcifications by distribution and morphology descriptor BI-RAD 4.

**The proposal:**

Let be A a k X m the matrix of morphological variable values for k suspicious object in g(x,y), B a n X m the proposed matrix, m the set of variables and n = 2^{m}, posibles values depending:

where li, lc, ls are minimal, central and maximun posible variable value. Additionally each row of B is previously labeled with 0 benign 1 malignant in the L set. The k-esime object in A, is classified Lk, if Akm = = Bkm