TOMOGRAPHIC RECONSTRUCTION USING FILTERED BACK-PROJECTION METHOD
Since its emergence in 1917, tomography become an important field that combine pure and applied mathematics. With tomography we can see a cross-sectional slice of an object without destroying the object. There are several methods for tomograpic reconstruction at this time, one of them is FBP (filter...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/18859 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Since its emergence in 1917, tomography become an important field that combine pure and applied mathematics. With tomography we can see a cross-sectional slice of an object without destroying the object. There are several methods for tomograpic reconstruction at this time, one of them is FBP (filtered back-projection) method. FBP method is considered as a fast and accurate reconstruction method in recent decades. In this final project, a discussion about the FBP method simulation to reconstruct a cross-sectional image from an object is performed and the filters are analized for obtaining a good reconstruction image. Filters that are used in the thesis are Ram-Lak filter, Shepp-Logan filter, Cosine filter, Hamming filter, Hann filter, and Blackman filter. The use of these filters affect the quality of the reconstruncted image. By using filter, the reconstructed image become an unblurred and clear image because these filters are high-pass filters or modified high-pass filters. The reconstructed images from each filter is analized by using SNR (signal to noise ratio), its frequency distribution, and by comparing its signal before and after filtering. Based on the analysis, it can be concluded that the Blackman filter produces the best image recontruction with SNR is 75,4768 dB |
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