Ultrasound Computed Tomography is a widely used technique for nondestructive control of materials. One application is the evaluation of the inner state of standing trees in urban areas. The quality of the tomographic image depends on several factors, such as the number of probes used and the image reconstruction algorithm. Here we are interested in evaluating the influence of using a reconstruction algorithm adapted to wood anisotropy, compared to the classic methods using an isotropic model, and the effect of numerically increasing the number of sensors and the time-of-flight measurements using an interpolation method, known as sinogram interpolation. A numerical configuration was tested, simulating the presence of an eccentric defect in a wood section. Reconstructed images were compared before and after the interpolation process, and a thresholding was applied to quantify the decay area estimation. A more detailed defect identification was obtained with the reconstruction algorithm adapted to wood anisotropy and the interpolation of the sensors.