Automatic local effect of window/level on 3D scale-space ellipsoidal filtering on run-off-arteries from white blood magnetic resonance angiography

Pre-filtering is a critical step in 3D segmentation of a blood vessel and its display. This paper presents the local effect of window/level over the 3D scale-space approach for filtering the white blood angiographic volumes and its implementation issues. The raw MR angiographic volume is first converted to an isotropic volume, then the window/level is automatically adjusted slice by slice and a composite volume is generated. 3D edges are then generated using separable Gaussian derivative convolution with known scales. The edge volume is then run by the directional processor at each voxel where the eigenvalues of the 3D ellipsoid are computed. The vessel score per voxel is then estimated based on these three eigenvalues which suppress the non-vasculature and background structures, yielding the filtered volume. The filtered volume is ray-cast to generate the maximum intensity projection images for display. The performance of the system is evaluated by computing the mean, variance, SNR and CNR images. We compare the filtering results with and without the usage of the local effect of window/level over 3D scale-space ellipsoidal filtering. We show that the automatic window/level is effective in detecting small vessels which are otherwise difficult to extrapolate. The system was run over 20 patient studies from different parts of the body such as brain, abdomen, kidney, knee, and ankle. The computer program takes around 150 seconds of processing time per study for a study with a data size of 512 × 512 × 194, which includes complete performance evaluation.