Abstract
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 based on using the first-order Bessel function of the first kind to relate the fields outside the imaged domain to the fields inside that domain. The predicted field distribution shows the relative differences between the dielectric properties of tissues within the torso and thus enables detecting lung cancer, which has a significantly larger dielectric constant that the lung's healthy tissues. To validate the proposed algorithm, an integrated imaging system, which includes a three-dimensional slot-rotated antenna that circularly scans an artificial torso phantom using the band 1.5-3 GHz, a wideband microwave transceiver and a laptop for control, processing and image generation, is built. The obtained experimental results confirm the reliability of the proposed method in lung cancer detection.
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