Average Subtraction Method for Image Reconstruction of Brain using ECVT for Tumor Detection

Maharani, Rizki dan Edison, Rizki Edmi dan Ihsan, Muhammad Fathul dan Taruno, Warsito Purwo (2020) Average Subtraction Method for Image Reconstruction of Brain using ECVT for Tumor Detection. International Journal of Technology, 11 (5). pp. 995-1004. ISSN 2086-9614

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Average Substraction Method for Image REconstruction of Brain using ECVT for Tumor Detection.pdf - Published Version

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Official URL: https://doi.org/10.14716/ijtech.v11i5.4325


Brain Electrical Capacitance Volume Tomography (Brain ECVT) is a new technique that realizes real-time volumetric imaging of dynamic changes in electrical activity of the brain and allows total interrogation of the whole volume inside a helmet-shaped sensor. The technique has been used for investigating numerous brain functional abnormalities, including brain tumors, based on permittivity different from the tumor case, as compared to the normal brain. However, interpretation of the conventional Brain ECVT image is not practical for clinical purposes, as the image resolutions are high in the cortical area and lower in the middle region. The technique provides relatively good sensitivity when the tumor is located near the cortex. In this study, we developed a novel method, namely the average subtraction technique, to process the reconstructed image of the brain obtained by Brain ECVT. The technique generates a three-dimensional intracranial distribution of permittivity that correlates with the electrical activity map of the brain with improved resolution in the center region of the brain. The technique provides better insight into brain intracranial electrical activity, which is quite distinctive when there is tumor development inside the brain. The technique may lead to better detection of brain tumors inside the brain based on the electrical activity scan.

Item Type: Article
Subjects: Q Science > Q Science (General)
Divisions: Fakultas Kedokteran
Depositing User: Rizki Edmi Edison
Date Deposited: 21 Dec 2020 04:55
Last Modified: 21 Dec 2020 04:55
URI: http://repository.uhamka.ac.id/id/eprint/4791

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