*2.1.2 Artifacts suppression and background separation*

In order to remove all unwanted objects in the selected image and separate the breast profile, we follow the next four steps:

Step (1) Thresholding of the mammogram image by 0.0706 normalized value.

**Figure 1.** *Flow chart of CAD system for breast cancer classification.*

In this chapter, we present a new algorithm for pectoral muscle suppression, this

*Medical Image Classification Using the Discriminant Power Analysis (DPA) of Discrete Cosine…*

operation is based on the Localization of the triangular region that contains the Pectoral Muscle, where the Seeded Region Growing (SRG) algorithm is invoked in

Step (6) *Apply the SRG in the upper left triangle ABC (that contains the Pectoral Muscle)*

Seeded Region Growing (SRG) is a useful image segmentation technique for medical images that is initially proposed by R. Adams et *al.* [28]. This technique is robust, fast and consists of three major steps: seed selection, region growing, and

The advantage of applying the (SRG) method into the localized triangular ABC

The Seed point is selected automatically by considering the results obtained from

**Figure 5(a)** shows the cropped image, where **Figure 5(b)** shows the selected region of interest (ROI). All obtained (ROI) images are resized in order to get the

region (**Figure 3**) is to remove only the pectoral muscle, without completely suppressing the triangular region as in some other methods. **Figures 3**–**5** show a

this operation.

region merging.

step (4) of algorithm 1.

same dimension.

**Figure 3.**

**53**

**Algorithm 1** Removal of the of pectoral muscle [15]

Step (1) *All the right MLO mammograms are left–right flipped* Step (2) *Divided MLO into four equal quadrants of 512x512 pixels.* Step (3) *The upper left quadrant is cropped with removing the left background*

Step (4) *The result is divided diagonally into two equal triangles.*

Step (7) *Re-Construct the Image and removing all backgrounds*

*Input: MLO mammograms size of 1024x1024*

*DOI: http://dx.doi.org/10.5772/intechopen.94026*

**Output:** The region of interest (ROI)

visual scheme of the proposed algorithm.

*Localization of the ABC triangle in the left upper quadrant.*

Step (5) *Select the Seed point*

**Figure 2.**

*The preprocessing steps of mammogram image: (a) original image, (b) noise removed image, (c) binary image, (d) largest area, (e) image right flipped, (f) parenchyma of the breast.*

Step (2) Mark all regions in the thresholded image (i.e., Artifacts, labels, … ). Step (3) Calculate the area of each region, and select the largest one. Step (4) The result of the step (3) is then used as a mask of the original grayscale mammography image.
