Mikrodalga Dielektrik Spektroskopi ile Yumuşak Doku Ossifikasyon Tespiti

Mikrodalga frekanslarında sert ve yumuşak dokular arasındaki dielektrik özellik farkı, yumuşak doku kemikleşme anomalilerinin teşhisi için kullanılanılabilme potansiyeline sahiptir. Biyolojik dokuların mikrodalga frekanslarda dielektrik özellikleri geleneksel olarak açık uçlu koaksiyel prob tekniği ile ölçülür. Bununla birlikle, doku heterojenitesi, kullanıcı hataları, matematiksel yaklaşım ve kalibrasyon bozulması nedeniyle kullanılan teknik yüksek hata oranlarına sahiptir. İyi ayrılmış bir veriye makine öğrenimi algoritması uygulandığında verinin yüksek doğrulukta sınıflandırılabileceği bilinmektedir. Bu nedenle, tekniğe özgü hatalardan en az etkilenebilecek bir sınıflandırma parametresinin seçilmesi, doku kategorizasyonunun doğruluğunu artırmak için kritiktir. Emprik olarak, mikrodalga frekanslarındaki dielektrik özellikler güç yasasına uyar. Bu olguya göre daha önce araştırılmamış bir parametre, dielektrik özelliklerden çıkarılabilecek güç parametresidir. Bu amaçla bu makale, yumuşak doku ossifikasyon anomalilerini tespit etmek için dielektrik özellik eğim değerlerinin sınıflandırılmasına dayalı bir ön çalışma sunmaktadır. Bu yaklaşım muhtemelen yüksek maliyetli görüntüleme ve mutasyon tarama testlerine alternatif bir hızlı tanı yöntemi olarak kullanılabilir. The dielectric property discrepancy between hard and soft tissues at microwave frequencies can potentially be utilized for the diagnosis of soft tissues ossification anomalies. Microwave dielectric properties of biological tissues are traditionally measured with the open-ended coaxial probe technique. However, the technıque 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:

Mikrodalga dielektrik özellikler, Cole-Cole denklemi, Güç yasası, Mikrodalga teşhis, Microwave dielectric properties, Cole-Cole equation, Power law, Microwave diagnostics

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