تفكيك ميكروكلسيفيكاسيون بافت پستان با روش ماموگرافي رقمي : ارايه يك روش پردازشي جديد

Discriminate of microcalcification in breast tissue with digital mammography: the presentation a new method of processing

Introduction. Techniques developed in computer and automated pattern recognition can be applied to assist radiologists in reading mammograms. With the introduction of direct digital mammography, this will become a feasible approach. A radiologist in breast cancer screening can use findings of computer as a second opinion, or as a pointer to suspicious regions. This may increase the sensitivity and specificity of screening programs and it may avoid the need for double reading. Materials and Methods. A program for detecting microcalcification clusters has performed, which discriminates clusters from normal breast tissue. First, we eliminated amorphous "clouds" or "blobs" in mammograms produced by normal paranchymal tissue of varying density using local average subtraction. Then we identified and removed the normal breast tissue. We have applied opening morphology operator and then, closing morphology in residual image. Any microcalcification that may exist in mammogram is therefore enhanced in the residual image, which makes the decision regarding the microcalcification of mammogram be much easier. The digital images were presented to radiologists before appling algorithm and after it. Results. Results of study show that sensitivity of this method in diagnosis is 100% against conventional mammogram (85.4%). Conclusion. Our results have demonstrated that this algorithm can be an effective aid to radiologists in the detection of a range of types of microcalcification in mammograms in an environment that is similar to routine clinical screening.