Almas Hilman Muhtadi, BS Thesis, Dept. of Physics, Bandung Institute of Technology, 2012
Brain is the most complicated organ in human body; it is an organ that related to human body sensory and control also most of the process in human body system, which is why brain is a very vital object to every human. Some dangerous illness is also related to brain abnormality such as brain cancer, schizophrenia, Alzheimer disease, etc. One way to monitor or diagnose this illness is only by checking the condition of the brain. To check the brain condition we must consider a method which is not harmful to the subject and also have minimal effect to the brain condition while it give us adequate information about the brain condition. That is why imaging technology become the solution for brain diagnosis. Many imaging technologies are being developed for this purpose such as MRI and fMRI. Electrical Capacitance Volume Tomography (ECVT) is one kind of imaging technology that was developed for process tomography, and just recently being applied in medical application. This technology is based on capacitance measurement between two electrodes surrounding the object. The capacity value is related to the electrical potential distribution and also the permittivity distribution of the object. The image generation is related to the permittivity distribution, which is obtained by solving the inverse problem with capacitance and sensitivity matrix information. Since brain is also an object that contains many tissues with different permittivity, it is possible to do brain imaging by using ECVT. In this research we want to test this hypothesis, we use EdWar Technology 32 Channel Helm Sensor and reconstructed the image in 32 × 32 × 32 pixel. The experiment is carried out in certain time interval, while we give certain mental task to the subject. We aim not only to get the image of the brain but also the brain activity related to certain activity in the time interval. From the experiment we successfully acquire a glimpse of human brain image and also the change of its condition in the time interval. The result is quite fair and still need many improvements.
Key Words: Brain Tomography, ECVT, Inverse Problem