Saat ini, komputasi tomografi (computed tomography/CT) sinar-X sudah banyak diterapkan di industri manufaktur untuk menguji atau memeriksa struktur internal suatu sampel. Metode Filtered Back Projecrtion (FBP) merupakan metode rekonstruksi citra CT yang popular digunakan untuk menghasilkan citra yang mempunyai noise lebih sedikit, kontras yang tajam dan mampu membedakan densitas antara latar belakang dan objek. Pemindaian citra digunakan mode geometri cone beam dengan rentang sudut 360° dan inkremen sudut 1°. Proses dimulai dari denoising, normalisasi, sintesis sinogram, dan rekonstruksi citra menggunakan FBP. Hasil dari penelitian ini adalah citra 2 dimensi hasil dari pemindaian citra geometri cone beam, sinogram dan hasil rekonstruksi citra irisan dengan parameter evaluasi yaitu Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), dan kontras relatif. Untuk mencari parameter evaluasi tersebut digunakan input koordinat Region of Interest (RoI). Diperoleh filter Cosine paling baik dalam memberikan nilai SNR, CNR dan kontras relatif paling tinggi. Dalam post processing akan digunakan variasi filter low pass (Ideal, Butterworth dan Gaussian). Input citra hasil rekonstruksi FBP menggunakan filter Cosine. Terdapat parameter evaluasi tambahan yaitu SSIM (Structural Similarity Index Measure). Beberapa parameter input seperti frekuensi cut-off, dan orde akan mempengaruhi frekuensi spasial. Frekuensi ini mengacu pada seberapa sering suatu gray value muncul atau berulang dalam citra.
Currently, X-ray computational tomography (CT) has been widely applied in the manufacturing industry to test or examine the internal structure of a sample. The Filtered Back Projection (FBP) method is a popular CT image reconstruction method used to produce images that have less noise, sharp contrast and are able to distinguish densities between the background and the object. Image scanning uses the cone beam geometry mode with an angle range of 360° and an angle increment of 1°. The process starts from denoising, normalizing, sinogram synthesis, and image reconstruction using FBP. The results of this study are 2-dimensional images resulting from scanning geometric cone beam images, sinograms and reconstructed sliced images with evaluation parameters namely Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), and relative contrast. To find the evaluation parameters, the Region of Interest (RoI) coordinate input is used. The Cosine filter is the best in providing the highest SNR, CNR and relative contrvalues. In post processing, variations of low pass filters (Ideal, Butterworth and Gaussian) will be used. Input the FBP reconstruction image using the Cosine filter. There is an additional evaluation parameter, namely SSIM (Structural Similarity Index Measure). Several input parameters such as cut-off frequency, and order will affect the spatial frequency. This frequency refers to how often a gray value appears or repeats in the image. |
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