Open AccessBRAIN TISSUES SEGMENTATION ON MR PERFUSION IMAGES USING CUSUM FILTER FOR BOUNDARY PIXELS
Author(s) -
Світлана Алхімова,
Andrii Krenevych
Publication year - 2019
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.18.2.1411
Subject(s) - segmentation , pixel , artificial intelligence , cusum , computer science , boundary (topology) , magnetic resonance imaging , computer vision , region of interest , perfusion , filter (signal processing) , point (geometry) , image segmentation , pattern recognition (psychology) , mathematics , medicine , radiology , mathematical analysis , statistics , geometry
The fully automated and relatively accurate method of brain tissues segmentation on Т2-weighted magnetic resonance perfusion images is proposed. Segmentation with this method provides a possibility to obtain perfusion region of interest in 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 Т2-weighted magnetic resonance perfusion images with abnormal brain anatomy.