Authors
Jesus Alejandro Martinez Juarez, Miraj Ud Din, Hui Jiang, Xiaohui Liu, Xuemei Wang
Published in
Progress in biomedical engineering (Bristol, England). Sep 28, 2026. Epub Sep 28, 2026.
Abstract
Cancer is a serious worldwide health issue. Routinary detection exams are recommended for better prognosis, however there are still no suitable routinary procedures. Electrical Impedance Tomography is a non-invasive, portable, low-cost novel imaging technology. Its side effects are reversible heat discomfort and/or uncomfortable electrostimulation. By measuring the dielectric properties of a region of interest, it makes possible to detect and monitor cancer. Software such as EIDORS and COMSOL are used nowadays to solve the forward and inverse problem. However, the state-of-the-art image reconstruction solutions are based on deep learning and this ongoing research has boosted the accuracy of EIT in a substantial manner. With such accuracy improvement, this technique has been utilized for breast cancer detection. The successful results for breast cancer encouraged researchers to explore its usage in other cancer types such as lung, skin, prostate, tongue and gynaecological. Results reaffirm that EIT holds great potential to be used in clinical cancer diagnostic scenarios and thus, more exhaustive research of EIT-based cancer imaging is highly recommended. This review offers an overview of the main elements that EIT technology comprises. Detailed explanation is provided for safety parameters and possible adverse effects. A comprehensive overview of deep tomographic image reconstruction in EIT is provided. Finally, an updated literature revision for EIT usage in the oncological area is presented.
PMID:
42805241
Bibliographic data and abstract were imported from PubMed on 29 Sep 2026.
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