An enhancement method for small brain metastases in T1w MRI

  • Authors:

  • Xing-Sheng Liu;Sheng-Dong Nie;Xi-Wen Sun

  • Affiliations:

  • School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China;School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China;Medical Imaging Department, Shanghai Pulmonary Hospital, Shanghai, China

  • Venue:
  • FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
  • Year:
  • 2009

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Abstract

Brain metastases(BM) are becoming an increasingly important cause of mortality among metastatic cancers, which accounts for over half of brain tumors. Early detection of brain metastases could have a significant impact on treatment outcomes and therefore essentially circumvent the spread of such tumors. In this work, a computerized image enhancement algorithm has been exploited to the benefit of improving detection of brain metastases. The algorithm first applied a clustering algorithm over each image pixel and then carried out the histogram normalization according to the parameters achieved by the clustering algorithm. Experimental results demonstrated that the contrast between BM and surrounding tissues was enhanced significantly by the proposed algorithm.