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Automated White Matter Hyperintensity Detection in Multiple Sclerosis Using 3D T2 FLAIR.
Zhong, Yi; Utriainen, David; Wang, Ying; Kang, Yan; Haacke, E Mark.
Afiliação
  • Zhong Y; School of Sino-Dutch Biomedical and Information Engineering, Northeastern University, Shenyang, Liaoning 110004, China ; Magnetic Resonance Innovations Inc., 440 E. Ferry Street, Detroit, MI 48202, USA.
  • Utriainen D; Magnetic Resonance Innovations Inc., 440 E. Ferry Street, Detroit, MI 48202, USA.
  • Wang Y; Department of Biomedical Engineering, Wayne State University, Detroit, MI 48201, USA.
  • Kang Y; School of Sino-Dutch Biomedical and Information Engineering, Northeastern University, Shenyang, Liaoning 110004, China.
  • Haacke EM; School of Sino-Dutch Biomedical and Information Engineering, Northeastern University, Shenyang, Liaoning 110004, China ; Magnetic Resonance Innovations Inc., 440 E. Ferry Street, Detroit, MI 48202, USA ; Department of Biomedical Engineering, Wayne State University, Detroit, MI 48201, USA ; Magnetic
Int J Biomed Imaging ; 2014: 239123, 2014.
Article em En | MEDLINE | ID: mdl-25136355
ABSTRACT
White matter hyperintensities (WMH) seen on T2WI are a hallmark of multiple sclerosis (MS) as it indicates inflammation associated with the disease. Automatic detection of the WMH can be valuable in diagnosing and monitoring of treatment effectiveness. T2 fluid attenuated inversion recovery (FLAIR) MR images provided good contrast between the lesions and other tissue; however the signal intensity of gray matter tissue was close to the lesions in FLAIR images that may cause more false positives in the segment result. We developed and evaluated a tool for automated WMH detection only using high resolution 3D T2 fluid attenuated inversion recovery (FLAIR) MR images. We use a high spatial frequency suppression method to reduce the gray matter area signal intensity. We evaluate our method in 26 MS patients and 26 age matched health controls. The data from the automated algorithm showed good agreement with that from the manual segmentation. The linear correlation between these two approaches in comparing WMH volumes was found to be Y = 1.04X + 1.74 (R (2) = 0.96). The automated algorithm estimates the number, volume, and category of WMH.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Guideline Idioma: En Revista: Int J Biomed Imaging Ano de publicação: 2014 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Guideline Idioma: En Revista: Int J Biomed Imaging Ano de publicação: 2014 Tipo de documento: Article País de afiliação: Estados Unidos