Abstract
The image processing of mammograms is very important for the early detection of breast pathologies, including cancer. This paper proposes a new technique based on directional fractal filtering for detecting microcalcification clusters or irregularly shaped microcalcifications. The proposed algorithm has two parts: a preprocessing step for detecting and locating microcalcification; and a second zooming, enhancement, and segmentation step. Detection is performed by image convolution using a set of masks with interesting fractal properties. Combined with other simple mathematical operations, remarkable contrast enhancement and segmentation are produced. The final result permits the clear delineation of the shape of individual microcalcifications. A comparison is made with other microcalcification enhancement techniques described in the literature.
Highlights
Microcalcifications are defined as calcium deposits inside the breast, which are associated with extra cell activity in breast tissue
All the processing steps were implemented as a simple macro digital mammograms
A novel mask convolution enhancement algorithm based on the fractal properties of a set of masks is presented
Summary
Microcalcifications are defined as calcium deposits inside the breast, which are associated with extra cell activity in breast tissue. Detecting microcalcifications is very difficult, and is more complicated in young women due to denser breast tissues, larger low-contrast areas, and highly correlated areas in mammograms This poses a very challenging task for radiologists. One main point of our approach is the conservation of the histogram into the zoomed images using the set of fractal masks This is possible thanks to the maximal distribution of gray pixel values over the mask area for a given number of pixels [13]. Visual segmentation is carried out by the XOR logical operator between both images Thanks to this visual zooming, enhancement, and segmentation, shapes and sizes of microcalcifications can be analyzed more and accurately by radiologists.
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