Noise filtering in thin-slice 4D Cerebral CT Perfusion scans

摘要

Patients suffering from cerebral ischemia or subarachnoid hemorrhage, undergo a 4D (3D+time) CT Perfusion (CTP) scan to assess the cerebral perfusion and a CT Angiography (CTA) scan to assess the vasculature. The aim of our research is to extract the vascular information from the CTP scan. This requires thin-slice CTP scans that suffer from a substantial amount of noise. Therefore noise reduction is an important prerequisite for further analysis. So far, the few noise filtering methods for 4D datasets proposed in literature deal with the temporal dimension as a 4th dimension similar to the 3 spatial dimensions, mixing temporal and spatial intensity information. We propose a bilateral noise reduction method based on time-intensity profile similarity (TIPS), which reduces noise while preserving temporal intensity information. TIPS was compared to 4D bilateral filtering on 10 patient CTP scans and, even though TIPS bilateral filtering is much faster, it results in better vessel visibility and higher image quality ranking (observer study) than 4D bilateral filtering.