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The fully automated and relatively accurate method of brain tissuessegmentation on T2-weighted magnetic resonance perfusion images is proposed.Segmentation with this method provides a possibility to obtain perfusion regionof interest on images with abnormal brain anatomy that is very important forperfusion analysis. In the proposed method the result is presented as a binarymask, which marks two regions: brain tissues pixels with unity values andskull, extracranial soft tissue and background pixels with zero values. Thebinary mask is produced based on the location of boundary between two studiedregions. Each boundary point is detected with CUSUM filter as a change pointfor iteratively accumulated points at time of moving on a sinusoidal-like pathalong the boundary from one region to another. The evaluation results for 20clinical cases showed that proposed segmentation method could significantlyreduce the time and efforts required to obtain desirable results for perfusionregion of interest detection on T2-weighted magnetic resonance perfusion imageswith abnormal brain anatomy.

Brain Tissues Segmentation on MR Perfusion Images Using CUSUM Filter for Boundary Pixels