TY - JOUR AU - ASLAN, Muhammet Fatih AU - Durdu, Akif AU - Sabanci, Kadir PY - 2019/12/12 Y2 - 2024/03/28 TI - Fusion of CT and MR Liver Images by SURF-Based Registration JF - International Journal of Intelligent Systems and Applications in Engineering JA - Int J Intell Syst Appl Eng VL - 7 IS - 4 SE - Research Article DO - 10.18201/ijisae.2019457233 UR - https://ijisae.org/index.php/IJISAE/article/view/1067 SP - 216-221 AB - <p>Medical imaging plays an important role in the diagnosis and treatment of different diseases. Images with more details are obtained by image fusion for more accurate analysis of medical images. In this study, Computed Tomography (CT) and Magnetic Resonance (MR) images of the liver from The Cancer Genome Atlas <em>Liver</em> Hepatocellular Carcinoma (TCGA-LIHC) are fused using different combinations of different wavelet types such as daubechies, coiflet and symlet. To accomplish this task, first the preprocessing steps are completed, and then registration is performed using Speed up Robust Features (SURF). As a result, to measure the quality of the obtained fusion image Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Structural Similarity Index Measurement (SSIM), Mean Structural Similarity (MSSIM) and Feature Similarity Index (FSIM) metrics are used.</p> ER -