T.V. Istomina, L.V Kuts, V.I. Petrov

In modern society, breast cancer in women is one of the most common diseases. For many years one of the most popular methods for early detection of breast cancer (BC) was a self-examination, self-control of the state of the mammary glands. Currently Mammography center screening, the most common method reveals a malignant tumor when it reaches a certain size. Therefore the main task - to provide early detection of cancer. Breast cancer usually begins with the appearance of its small thickness, perfectly smooth bounded compaction, which is very often the patient discovers by accident, feeling his chest. Compaction generally hilly, with different values depending on the stage of the disease. Therefore, the full range of diagnostic procedures in mammalogy is aimed primarily at identifying breast cancer. It is known that cancer has a higher temperature than the surrounding tissues. These data were first obtained by the French scientist M. Guture, who spent more than 550 invasive measurements showed that the tumor temperature is determined by its doubling time [1]. Therefore, the most dangerous, fast-growing tumors have a very high temperature. It is also known that thermal changes precede structural changes. In particular, the thermal changes of mammary glands occur not at the moment when the cancer reaches the required size, but much earlier. Many authors classify this condition as precancerous. Currently, there are gentle way to detect temperature anomalies of internal tissues, using the diagnostic RTM-01-RES. This research method, called microwave mammography or RTM-diagnosis, based on measuring the natural electromagnetic radiation from breast tissue in the microwave and infrared range [1]. It is known that the thermal radiation power is proportional to the temperature of tissues. Therefore, measuring the radiation power of tissues in the microwave range allows to detect thermal changes at a depth of several centimeters. Since many medical signals are nonstationary, it is necessary to use methods to select informative component of the signal against the background of uninformative, pattern recognition and detection of key diagnostic features, as well as for image compression with minimal loss of diagnostic information [2]. For the analysis of these signals requires a method that can provide good resolution both in frequency and in time. The first thing you want to localize low-frequency components, the second - for the resolution of high frequency components. This method is the wavelet transform (WT). For the experiment, the signal was simulated in the mathematical package MatLab. As the results of the experiment, the application of the WT [3] to select the informative component of the signal give quality results.