Research On ERT Algorithm Of Cancer Tissue In Human Lungs

Electrical tomography technology(ET) is an advanced process tomography technology. Compared with the existing visualization technology such as CT, ET technology has the advantages of: nonradioactive, non-intrusive, low cost. As a result, ET technology has broad applying prospect and huge potential in many key areas such as industrial inspection and medical bed real-time monitoring.1) Analyzing with the thought of” multiple iterations under first-order approximation”, imaging with the methods of back projection and kinds of iterative algorithm, we can conclude that the result solved from the correction within the framework of” multiple iterations under first-order approximation” can't meet the image quality requirement. Following this thought, we can't improve the quality of ET technology significantly.2) Focusing on the low availability of measuring data, the research analyzed the distribution of the measuring data in 16 electrodes model. Basing on the research we found the difference between the valuable data is so small that the worth message was flooded. Data preprocessing is needed to improve the availability of measuring data. Based on the above analysis, this paper presents a kind of data preprocessing methods to the measuring data. It shows that opening five powers could obtain the best imaging results, and the paper verifies the effectiveness through a variety of models.3) Focusing on the definition of sensitivity coefficient isn't intuitive, the research analyzed the distribution of sensitivity coefficient in 16 electrodes model; basing on polarity effect, the research proposed a kind of sensitivity coefficient solution method. This method abandoned the complex integral form and defined the sensitivity coefficient with the message of position. As a result, the solution process of sensitivity coefficient is more intuitive; in addition, the sensitivity coefficient solved with the new method has no relation with the distribution of conductivity. At the end of this part, the article demonstrated the correctness of the method and deduced the new result of potential allelic area.