ArticleSensors (Basel, Switzerland)2019
A Lagrange-Newton Method for EIT/UT Dual-Modality Image Reconstruction.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Posterior Approximate Clustering-Based Sensitivity Matrix Decomposition for Electrical Impedance Tomography.Sensors (Basel, Switzerland) · 2024Article
- Reconstruction of conductivity distribution with electrical impedance tomography based on hybrid regularization method.Journal of medical imaging (Bellingham, Wash.) · 2021Article
- Anomaly Detection Using Electric Impedance Tomography Based on Real and Imaginary Images.Sensors (Basel, Switzerland) · 2020Article
- Selected Papers from the 9th World Congress on Industrial Process Tomography.Sensors (Basel, Switzerland) · 2019Article
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4 authors.
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Abstract
An image reconstruction method is proposed based on Lagrange-Newton method for electrical impedance tomography (EIT) and ultrasound tomography (UT) dual-modality imaging. Since the change in conductivity distribution is usually accompanied with the change in acoustic impedance distribution, the reconstruction targets of EIT and UT are unified to the conductivity difference using the same mesh model. Some background medium distribution information obtained from ultrasound transmission and reflection measurements can be used to construct a hard constraint about the conductivity difference distribution. Then, the EIT/UT dual-modality inverse problem is constructed by an equality constraint equation, and the Lagrange multiplier method combining Newton-Raphson iteration is used to solve the EIT/UT dual-modality inverse problem. The numerical and experimental results show that the proposed dual-modality image reconstruction method has a better performance than the single-modality EIT method and is more robust to the measurement noise.
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