<p>Technologies in image acquisition have developed and often provide image volumes in more than two dimensions. Computer tomography and magnet resonance imaging provide image volumes in three spatial dimensions. The image enhancement methods have developed as well and in this thesis work 3D image enhancement with filter networks is evaluated.</p><p>The aims of this work are; to find a method which makes the initial parameter settings in the 3D image enhancement processing easier, to compare 2D and 3D processed image volumes visualized with different visualization techniques and to give an illustration of the benefits with 3D image enhancement processing visualized using these techniques.</p><p>The results of this work are;</p><p>1. a parameter setting tool that makes the initial parameter setting much easier and</p><p>2. an evaluation of 3D image enhancement with filter networks that shows a significant enhanced image quality in 3D processed image volumes with a high noise level compared to the 2D processed volumes. These results are shown in slices, MIP and volume rendering. The differences are even more pronounced if the volume is presented in a different projection than the volume is 2D processed in.</p>

Technologies in image acquisition have developed and often provide image volumes in more than two dimensions. Computer tomography and magnet resonance imaging provide image volumes in three spatial dimensions. The image enhancement methods have developed as well and in this thesis work 3D image enhancement with filter networks is evaluated. The aims of this work are; to find a method which makes the initial parameter settings in the 3D image enhancement processing easier, to compare 2D and 3D processed image volumes visualized with different visualization techniques and to give an illustration of the benefits with 3D image enhancement processing visualized using these techniques. The results of this work are; 1. a parameter setting tool that makes the initial parameter setting much easier and 2. an evaluation of 3D image enhancement with filter networks that shows a significant enhanced image quality in 3D processed image volumes with a high noise level compared to the 2D processed volumes. These results are shown in slices, MIP and volume rendering. The differences are even more pronounced if the volume is presented in a different projection than the volume is 2D processed in.