Automated cervical cancer detection using photonic crystal based bio-sensor

In this paper we are going to propose a logic by simulation, that an automatic system for detection of cervical cancer based on spectrum obtained from photonic crystal based bio-sensor, is possible. A 2-dimensional photonic crystal based bio-sensor in a static environment under the influence of electromagnetic radiation, whose range spans from UV to IR, designed to be highly sensitive for the changes in the dielectric constant e under the applied electric and magnetic induction for a set of concentration ranges of the analyte. As the refractive index of normal and cancer infected tissue is inferred, the sensor can easily differentiate normal tissue and cancer infected cervical tissue. The output of the sensor is known to exhibit distinct signatures in the frequency and amplitude spectra even while slight changes in the refractive index of the cervical cell takes place. A machine learning technique Naïve Bayesian classifier is used to distinguish the normal and cancerous tissue spectrum based on automatically extracted parameters of the attributed sensor output. The combined amalgamation of the sensor data and the incorporated automated classification archive into photonic crystal based bio-sensor, achieves better performance in detecting cervical cancer.