Modeling and imaging of intestinal electrical impedance based on conjugate gradient method

Colorectal disease is a digestive tract disease of high incidence worldwide. Its preliminary diagnosis methods such as anal digital diagnosis and enteroscopy are somewhat subjective. Moreover, it is difficult to locate precisely the lesions and their infiltration boundaries for an accurate diagnosis of disease. This study combines endoscope with electrodes placed on the inner wall of the intestine to obtain both the traditional image of the intestine lumen and its electrical impedance tomography (EIT). The spatial impedance distribution image is reconstructed from the data collected by different combination of excitation and detection electrodes. The multidimensional and multiparameter intestinal physiological and pathological changes can thus be analyzed by EIT. This study mainly consists of the following three contributions: (a) construct certain physical models that reflect corresponding characteristics of intestinal tissue and its pathological changes; (b) optimize targeted signal acquisition methods suitable for data processing and analysis of intestinal cavity; and (c) establish a method of image reconstruction that conforms to the morphological characteristics of the intestinal cavity, so that comparative analysis can be applied by using different algorithms for image reconstruction. Through the extraction and analysis of impedance information for intestinal characteristics, we aim to make this tool a supplementary diagnosis method of high sensitivity and specificity for related diseases. This may lay a foundation for more accurate clinical screening of high‐risk population, more precise diagnosis and localization of lesion characteristics, and thus better treatment guidance. In this study, electrical impedance technique was used to obtain the functional image of the intestine. The image reconstruction is different from the traditional ways, which detection and image reconstruction is an annular region that extends outward, hence the algorithm analysis and design based on this method are exploratory. As a diagnostic method with high sensitivity and specificity, this technology is of great significance for early screening of diseases, identification, and localization of tissue characteristics.