The research paper titled A High-resolution Image Reconstruction Method of Lung Nodules with B-spline based Whale Optimization Algorithm (B-WOA) for Electrical Impedance Tomography has been accepted by the journal IEEE Transactions on Instrumentation and Measurement.
The paper proposes a method using the B-spline based Whale Optimization Algorithm (B-WOA) for high-resolution image reconstruction of lung nodules using Electrical Impedance Tomography (EIT). This method maps the target positions to the conductivity distribution using B-spline curves and establishes an optimized objective function using the sensitivity matrix method. The lung nodule images are then reconstructed using the WOA algorithm. The quality of the reconstructed images using WOA is compared with three traditional algorithms through numerical simulations on randomly generated lung nodule models. The simulation results show that the average image correlation coefficient of the reconstructed images using WOA is improved by 4.8% compared to the best-performing traditional algorithm, Tikhonov regularization. Additionally, an experimental model of lung nodules is established to validate the proposed method. Different diameters of biological tissues are used to simulate the lung nodule region. The performance of WOA, Tikhonov regularization, and Genetic Algorithm (GA) is studied in a dual-objective imaging experiment. The experimental results demonstrate that the average ICC values of the reconstructed images using WOA are increased by 4.7% and 3.5% compared to Tikhonov regularization and GA, respectively. Therefore, the proposed B-WOA method enables high-resolution imaging of small target distributions and holds promise for clinical detection of lung nodules.
