Automatic Segmentation of MRI Images in Dynamic Programming Mode.

Objective: Purpose of this work was to develop methods contour and volume of areas of interest definition in tomographic images of the breast. Methods: The study included images of the breast of 13 patients obtained on an open electronic resource The Breast-MRI-NACT-Pilot image collection. Statistical processing of the data was carried out, the reliability of the results of calculating the volumes of the breast areas was estimated, a visual evaluation of the obtained numerical values was provided – a linear graph. Result: A program for automatic determination of breast volume and volume of pathology has been developed and tested. For segmenting areas of the breast, a threshold segmentation and a managed watershed method programs were written in Matlab package. The developed programs allowed to obtain reliable data when processing MRI images of the breast of 13 patients. Results of using Hurst exponent show that in the case of a pathology, the exponent is less than 0.4, and for the tissue without pathology the Hurst index is greater than 0.4. This method is implemented in dynamic programming mode, which allows to adjust the algorithm for a task of examining images. Conclusion: The developed methods of definition of contours and calculating volumes allow an automatic quantitative evaluation of the ratio of the volumes of different identified areas of interest in the postprocessing of MRI images. Also, the results have established that it is possible to use the Hurst exponent as an additional tool for identifying pathologies in areas of interest.