title: Automated quantification of white matter lesion in magnetic resonance imaging of patients with acute infarction.
abstract: OBJECTIVE
  It has been reported that increased white matter lesions (WML) is one of the risk factors for stroke. To quantify WML objectively with the presence of acute infarcts, we proposed an automated segmentation scheme to locate WMLs in combined T1-weighted MRI, fluid attenuation inversion recovery (FLAIR) and diffusion weighted imaging (DWI).
  
  
  METHODS
  The proposed method detects WMLs by a coarse-to-fine mathematical morphology method. It has been evaluated quantitatively and qualitatively using voxel-based, volume-based, score-based, and atlas-based approaches on MRI data of 91 subjects with acute infarction.
  
  
  RESULTS
  The proposed WML detection algorithm yields average sensitivity, positive predictive value and similarity index of 0.803, 0.818, and 0.836, respectively. Experimental results demonstrated that the segmentation from the proposed method is in high agreement with that from manual segmentation (intraclass correlation coefficient=0.9892), and with a good correlation with visual scores (R=0.8442, p<0.0001).
authors.affiliation: Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.
authors.forename: Lin
authors.initials: L
authors.lastname: Shi
authors.forename: Defeng
authors.initials: D
authors.lastname: Wang
authors.forename: Shangping
authors.initials: S
authors.lastname: Liu
authors.forename: Yuehua
authors.initials: Y
authors.lastname: Pu
authors.forename: Yilong
authors.initials: Y
authors.lastname: Wang
authors.forename: Winnie C W
authors.initials: WC
authors.lastname: Chu
authors.forename: Anil T
authors.initials: AT
authors.lastname: Ahuja
authors.forename: Yongjun
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000368:Aged; D000465:Algorithms; D001331:Automation; D001921:Brain / Q000473:pathology*; D002544:Cerebral Infarction / Q000473:pathology*; D038524:Diffusion Magnetic Resonance Imaging; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D015588:Observer Variation