Lung cancer detection using frequency-domain microwave imaging


A frequency-domain algorithm for the early detection of lung cancer is presented. The algorithm predicts the distribution of scattered fields inside the imaged domain (torso) using the measured fields around that domain. That prediction is predicated on using the primary-order Bessel function of the first kind to relate the fields outside the imaged domain to the fields within that domain. The predicted field distribution shows the relative variations between the dielectric properties of tissues within the torso and so enables detecting lung cancer, that includes a significantly larger dielectric constant that the lung's healthy tissues. To validate the proposed algorithm, an integrated imaging system, that includes a 3-dimensional slot-rotated antenna that circularly scans a synthetic torso phantom using the band 1.5-three GHz, a wideband microwave transceiver and a laptop for control, processing and image generation, is built. The obtained experimental results make sure the reliability of the proposed methodology in lung cancer detection.

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