ANALISIS PERBANDINGAN CITRA ECVT (ELECTRICAL CAPACITANCE VOLUME TOMOGRAPHY) BRAIN SCANNER DENGAN METODE REKONSTRUKSI CITRA ITERATIVE LINEAR BACK PROJECTION (ILBP) DAN NEURAL-NETWORK MULTI-CRITERIA OPTIMIZATION IMAGE RECONSTRUCTION TECHNIQUE (NN-MOIRT)

KHARISMA FAJAR HIDAYANTI , NIM. 09620017 (2014) ANALISIS PERBANDINGAN CITRA ECVT (ELECTRICAL CAPACITANCE VOLUME TOMOGRAPHY) BRAIN SCANNER DENGAN METODE REKONSTRUKSI CITRA ITERATIVE LINEAR BACK PROJECTION (ILBP) DAN NEURAL-NETWORK MULTI-CRITERIA OPTIMIZATION IMAGE RECONSTRUCTION TECHNIQUE (NN-MOIRT). Skripsi thesis, UIN SUNAN KALIJAGA.

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	Text ( ANALISIS PERBANDINGAN CITRA ECVT (ELECTRICAL CAPACITANCE VOLUME TOMOGRAPHY) BRAIN SCANNER DENGAN METODE REKONSTRUKSI CITRA ITERATIVE LINEAR BACK PROJECTION (ILBP) DAN NEURAL-NETWORK MULTI-CRITERIA OPTIMIZATION IMAGE RECONSTRUCTION TECHNIQUE (NN-MOIRT) ) BAB II, III, IV.pdf Restricted to Registered users only Download (4MB)

Abstract

Electrical Capacitance Volume Tomography (ECVT) is an electrical tomography techniques based on capacitance measurement that generates volumetric image of the region enclosed by the geometrically three-dimensional capacitance sensor. Currently, ECVT has been applied to reconstruct human brain activity. The electrical signals of brain are mapped by ECVT in 3D images real time. In the reconstruction process of ECVT, algorithm technique is very important role. In this study, has been carried simulation of ECVT for brain scanner with 32 electrodes. The image of ECVT obtained using Iterative Linear Back Projection (ILBP) dan Neural-Network Multi-Criteria Optimization Image Reconstruction Technique (NN-MOIRT) technique. Simulation carried with varied the position object, number of object and simulation object which given charge density in sensor. From this study, unknown that the NN-MOIRT technique more convergent, more stable when image reconstruction and more capable illustrate the image of object condition approach obvious than ILBP technique.

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