Oumaima Bader;Hanyu Yang;Mariem Hafsa;Najoua Essoukri Ben Amara;Olfa Kanoun
{"title":"基于旋转径向注射的增强电阻抗断层扫描:电仿生胸体的定量研究","authors":"Oumaima Bader;Hanyu Yang;Mariem Hafsa;Najoua Essoukri Ben Amara;Olfa Kanoun","doi":"10.1109/LSENS.2025.3591271","DOIUrl":null,"url":null,"abstract":"Identifying the optimal current injection pattern is crucial in electrical impedance tomography (EIT) to improve image reconstruction accuracy. This study compares the performance of a newly proposed rotating radial current injection pattern with the commonly used in EIT, which are the adjacent and opposite injection patterns. The evaluation is realized on a biomimetic thorax-shaped resistor mesh phantom by evaluating quantitative metrics derived from measured boundary voltages, including condition number (<inline-formula><tex-math>$k$</tex-math></inline-formula>), dynamic range (DR), and mean sensitivity (<inline-formula><tex-math>$S$</tex-math></inline-formula>). The investigation is based on the evaluation of the image correlation coefficient (ICC) and the structural similarity index measure <inline-formula><tex-math>$(SSIM)$</tex-math></inline-formula>, comparing reconstructed images from simulation and measurement data to assess reconstruction accuracy. Results demonstrate that the rotating radial pattern achieves an ICC of 0.98, an SSIM of 0.82, a lower <inline-formula><tex-math>$k$</tex-math></inline-formula>, a higher <inline-formula><tex-math>$S$</tex-math></inline-formula>, and an increased DR compared to the adjacent and opposite patterns. These findings highlight the potential of the rotating radial pattern to advance EIT imaging performance for diverse applications in lung imaging.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"9 9","pages":"1-4"},"PeriodicalIF":2.2000,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhanced Electrical Impedance Tomography Using Rotating Radial Injection: A Quantitative Study on an Electrical Biomimetic Thoracic Phantom\",\"authors\":\"Oumaima Bader;Hanyu Yang;Mariem Hafsa;Najoua Essoukri Ben Amara;Olfa Kanoun\",\"doi\":\"10.1109/LSENS.2025.3591271\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Identifying the optimal current injection pattern is crucial in electrical impedance tomography (EIT) to improve image reconstruction accuracy. This study compares the performance of a newly proposed rotating radial current injection pattern with the commonly used in EIT, which are the adjacent and opposite injection patterns. The evaluation is realized on a biomimetic thorax-shaped resistor mesh phantom by evaluating quantitative metrics derived from measured boundary voltages, including condition number (<inline-formula><tex-math>$k$</tex-math></inline-formula>), dynamic range (DR), and mean sensitivity (<inline-formula><tex-math>$S$</tex-math></inline-formula>). The investigation is based on the evaluation of the image correlation coefficient (ICC) and the structural similarity index measure <inline-formula><tex-math>$(SSIM)$</tex-math></inline-formula>, comparing reconstructed images from simulation and measurement data to assess reconstruction accuracy. Results demonstrate that the rotating radial pattern achieves an ICC of 0.98, an SSIM of 0.82, a lower <inline-formula><tex-math>$k$</tex-math></inline-formula>, a higher <inline-formula><tex-math>$S$</tex-math></inline-formula>, and an increased DR compared to the adjacent and opposite patterns. These findings highlight the potential of the rotating radial pattern to advance EIT imaging performance for diverse applications in lung imaging.\",\"PeriodicalId\":13014,\"journal\":{\"name\":\"IEEE Sensors Letters\",\"volume\":\"9 9\",\"pages\":\"1-4\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Sensors Letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11087632/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11087632/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Enhanced Electrical Impedance Tomography Using Rotating Radial Injection: A Quantitative Study on an Electrical Biomimetic Thoracic Phantom
Identifying the optimal current injection pattern is crucial in electrical impedance tomography (EIT) to improve image reconstruction accuracy. This study compares the performance of a newly proposed rotating radial current injection pattern with the commonly used in EIT, which are the adjacent and opposite injection patterns. The evaluation is realized on a biomimetic thorax-shaped resistor mesh phantom by evaluating quantitative metrics derived from measured boundary voltages, including condition number ($k$), dynamic range (DR), and mean sensitivity ($S$). The investigation is based on the evaluation of the image correlation coefficient (ICC) and the structural similarity index measure $(SSIM)$, comparing reconstructed images from simulation and measurement data to assess reconstruction accuracy. Results demonstrate that the rotating radial pattern achieves an ICC of 0.98, an SSIM of 0.82, a lower $k$, a higher $S$, and an increased DR compared to the adjacent and opposite patterns. These findings highlight the potential of the rotating radial pattern to advance EIT imaging performance for diverse applications in lung imaging.