2 research outputs found
Brain Tissues Segmentation on MR Perfusion Images Using CUSUM Filter for Boundary Pixels
The fully automated and relatively accurate method of brain tissues
segmentation on T2-weighted magnetic resonance perfusion images is proposed.
Segmentation with this method provides a possibility to obtain perfusion region
of interest on images with abnormal brain anatomy that is very important for
perfusion analysis. In the proposed method the result is presented as a binary
mask, which marks two regions: brain tissues pixels with unity values and
skull, extracranial soft tissue and background pixels with zero values. The
binary mask is produced based on the location of boundary between two studied
regions. Each boundary point is detected with CUSUM filter as a change point
for iteratively accumulated points at time of moving on a sinusoidal-like path
along the boundary from one region to another. The evaluation results for 20
clinical cases showed that proposed segmentation method could significantly
reduce the time and efforts required to obtain desirable results for perfusion
region of interest detection on T2-weighted magnetic resonance perfusion images
with abnormal brain anatomy