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Method of Improved Fuzzy Contrast Combined Adaptive Threshold in NSCT for Medical Image Enhancement.

Noises and artifacts are introduced to medical images due to acquisition techniques and systems. This interference leads to low contrast and distortion in images, which not only impacts the effectiveness of the medical image but also seriously affects the clinical diagnoses. This paper proposes an a...

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Published in:BioMed Research International Vol. 2017; pp. 1 - 11
Main Authors: Zhou, Fei, Jia, ZhenHong, Yang, Jie, Kasabov, Nikola
Format: diagnostic images equations & formulas research tables/charts Journal Article
Published: Wiley-Blackwell 6/28/2017
Online Access:View this record in EBSCOhost
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      jtl: BioMed Research International
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      dt: 6/28/2017
      vid: 2017
      pid: 480
      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2017/3969152
        123822714
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        atl: Method of Improved Fuzzy Contrast Combined Adaptive Threshold in NSCT for Medical Image Enhancement.
      aug:
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          Zhou, Fei
          Jia, ZhenHong
          Yang, Jie
          Kasabov, Nikola
        affil: College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China
      sug:
        subj:
          Diagnostic Imaging Evaluation
          Science
          Contrast Media
          Artifacts
          Tomography, X-Ray Computed
          Data Analysis Software
      ab: Noises and artifacts are introduced to medical images due to acquisition techniques and systems. This interference leads to low contrast and distortion in images, which not only impacts the effectiveness of the medical image but also seriously affects the clinical diagnoses. This paper proposes an algorithm for medical image enhancement based on the nonsubsampled contourlet transform (NSCT), which combines adaptive threshold and an improved fuzzy set. First, the original image is decomposed into the NSCT domain with a low-frequency subband and several high-frequency subbands. Then, a linear transformation is adopted for the coefficients of the low-frequency component. An adaptive threshold method is used for the removal of high-frequency image noise. Finally, the improved fuzzy set is used to enhance the global contrast and the Laplace operator is used to enhance the details of the medical images. Experiments and simulation results show that the proposed method is superior to existing methods of image noise removal, improves the contrast of the image significantly, and obtains a better visual effect.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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