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Segmentation and quantification of ischemic lesions on DWI images with different b-value at high magnetic field (3.0T)

  • Wu Li
  • , Jie Tian*
  • , Jianping Dai
  • *Corresponding author for this work
  • CAS - Institute of Automation
  • Capital Medical University

Research output: Contribution to journalConference articlepeer-review

Abstract

Diffusion weighted imaging (DWI) is the gold standard for imaging of acute stroke. Today, high-field systems operating at 3T become increasingly available in clinical settings. But, with b-value increasing, lesion SNR of DWI image descends, and anisotropy increases significantly. Aim of the study is to develop an automatic volumetric measure method of ischemic lesions on diffusion weighted imaging (DWI) images at high magnetic field, without the disturbance of anisotropy. Using a home-built interactive platform, we rated SNR and anisotropy. The extent of anisotropy was evaluated by the intensity ratio of white matter versus gray matter. Based on this knowledge, we developed an automatic segmentation method, involving firstly non-linear anisotropic diffusion filtering, secondly expert pieces of information applied to determine the scopes of parameters according to different b-value, and finally multi-scale adaptive statistical classification with intensity inhomogeneity correction. Results of the automatic segmentation are compared with lesion delineations by experts, showing the rapid identification of ischemic lesion with accuracy and reproducibility, even in the presence of radio frequency (RF) inhomogeneity. There has been considerable interest in using DWI at 3T to detect ischemic lesion in stroke patients. The proposed method is promising for rapid, accurate, and quantitatively diagnosis of ischemic stroke.

Original languageEnglish
Pages (from-to)613-622
Number of pages10
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5369
DOIs
StatePublished - 2004
Externally publishedYes
EventMedical Imaging 2004: Physiology, Function, and Structure from Medical Images - San Diego, CA, United States
Duration: 15 Feb 200417 Feb 2004

Keywords

  • DWI
  • Image segmentation
  • Intensity inhomogeneity
  • Ischemic lesion
  • Statistical classification

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