Abstract
The proposed work focuses on the detection of lung cancer using a microstrip patch antenna. A compact microstrip patch antenna operating at ISM band has been designed and placed on healthy as well as cancer affected lung (different stages) phantom. Scatter and other parameters are observed, and data set is created for healthy as well as for each stage of cancerous lung. Variation because of cancer and its stages in the antenna parameters such as electric field, magnetic field, surface current, power flow, current density, power loss density, electrical energy density, and magnetic energy density, return loss, antenna gain, and tumor radius is observed. The created dataset has been further classified to differentiate a healthy lung from a cancerous one and its stages using Random Forest machine learning algorithm with an accuracy of 93.75%.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
