A Modified Exact Reconstruction Algorithm to Determine the Complex Permittivity Perturbations of a Cancer-Affected Biological Target Using the Microwave Tomography Technique
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Abstract
As an emerging technology, the microwave tomography technique (MTT) is demonstrating its effectiveness in detecting cancer at an early stage. Due to the random, non-deterministic characteristics of cancer cells, more advancements are required in MTT to accurately detect the presence and location of the affected region. In this paper, we consider this fundamental issue and propose a modified exact reconstruction algorithm (mERA) capable of providing a detailed analysis of all kinds of complex dielectric perturbations in any cancer-affected biological target. In MTT, the detection of a cancerous tumor inside any organ of the human body is performed using different image reconstruction algorithms. In contrast, the proposed algorithm in this study uses a selective data segregation mechanism to generate the perturbed complex cell permittivity of the affected organ tissues. The efficiency of our approach in detecting all types of dielectric variations such as large (20%), small (5%), positive or negative has also been verified, even in a mixed scenario where affected cells possess all types of perturbations simultaneously. As a cancerous cell shows peculiar behavior inside the human body and its nature varies from person to person and even in between the different stages (1, 2, 3, and 4) of cancer, the algorithm is designed in such a way that it can detect the presence of a tumor taking all these possibilities into account. The results validate the high accuracy and effectiveness of the proposed mERA in the field of cancer diagnosis.
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