Özet:

The dielectric characteristic difference between hard and soft tissues in microwave frequencies has the potential to be used for the diagnosis of soft tissue osteoporosis anomalies. The dielectric properties of biological tissues in microwave frequencies are traditionally measured by the open-end coactional prob technique. In addition, the technique used due to the heterogeneity of the tissue, user errors, mathematical approach and calibration disorders has high errors. It is known that when a well-distributed data is applied by a machine learning algorithm, the data can be classified with high accuracy. Therefore, the selection of a classification parameter that may be at least affected by technical errors is critical to increase the accuracy of the tissue classification. In empirical terms, the dielectrial characteristics in microwave frequencies adhere to the law of power. According to this fact, a parameters not previously studied are the power parameters that can be extracted from dielectrial properties. For this purpose, this article provides a preliminary study based on the classification of the curved values of dielectrial characteristics to detect soft tissue ossification anomalies. This approach is likely to be used as an alternative to high-cost visualization and mutation scan tests. The dielectric property discrepancy between hard and soft tissues at microwave frequencies can potentially be used for the diagnosis of soft tissue ossification anomalies. Microwave dielectric properties of biological tissues are traditionally measured with the open-ended coaxial probe technique. However, the technik suffers from high error rates due to tissue heterogeneity, user errors, mathematical approach and calibration degredation. It is known that a well seperated data can be classified with high accuracy when a machine learnin algorithm is applied. Therefore, choosing a classification parameter that can be least affected by inherent errors is critical for increasing the accuracy of tissue categorization. Emprically, dielectric properties at microwave frequencies abides by the power law. Based on this fact, one unexplored parameter is the power parameter which can be derived from the dielectric properties. To this end, this work presents a preliminary study based on classification of dielectric property slope values to detect the soft tissue ossification anomalies. This approach can possibly be used as an alternative rapid diagnostic method to highcost imaging and mutation screening tests.

Anahtar Kelimeler: