Image Reconstruction for Electromagnetic Tomography Based on Improved Cuckoo Search Algorithm

Electromagnetic tomography (EMT) is a promising and flexible technique for imaging conductivity and/or permeability because of its noncontact nature.However, the EMT inverse problem is both ill-posed and ill-conditioned because of the soft-field nature of the electromagnetic field and the limited prior information, which significantly impacts imaging quality.To overcome this challenge, an improved Cuckoo Search algorithm is introduced, incorporating a dynamic adaptive mechanism to adjust the discovery probability P and adaptive step size .This modification improves the search capability, leading to higher optimization accuracy and faster convergence.Numerical simulations demonstrate that the proposed algorithm outperforms other classical techniques, particularly in terms of typical conductivity distributions.Further validation using the developed modular EMT system confirms the superior imaging performance of the method, making it a promising candidate for practical EMT applications.

Authors

Publication Details

Journal
Sensors and Materials
Published
2026-04-01
DOI
https://doi.org/10.18494/sam5816
Primary Topic
Electrical and Bioimpedance Tomography
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Image Reconstruction for Electromagnetic Tomography Based on Improved Cuckoo Search Algorithm

Yue Yang, Xianglong Liu, Ying Wang
Sensors and Materials
Electrical and Bioimpedance Tomography
article

Image Reconstruction for Electromagnetic Tomography Based on Improved Cuckoo Search Algorithm

Yue Yang, Xianglong Liu, Ying Wang
article en

Abstract

Electromagnetic tomography (EMT) is a promising and flexible technique for imaging conductivity and/or permeability because of its noncontact nature.However, the EMT inverse problem is both ill-posed and ill-conditioned because of the soft-field nature of the electromagnetic field and the limited prior information, which significantly impacts imaging quality.To overcome this challenge, an improved Cuckoo Search algorithm is introduced, incorporating a dynamic adaptive mechanism to adjust the discovery probability P and adaptive step size .This modification improves the search capability, leading to higher optimization accuracy and faster convergence.Numerical simulations demonstrate that the proposed algorithm outperforms other classical techniques, particularly in terms of typical conductivity distributions.Further validation using the developed modular EMT system confirms the superior imaging performance of the method, making it a promising candidate for practical EMT applications.

Sensors and MaterialsVol. 38(4)
National Natural Science Foundation of China, Zhengzhou University, Natural Science Foundation of Henan Province
Openalex Percentile: Top 23%
Electrical and Bioimpedance Tomography
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.