An adaptive enhancement method for breast X-ray images based on the nonsubsampled contourlet transform domain and whale optimization algorithm.

We propose a new method for breast X-ray image adaptive enhancement that combines nonsubsampled contourlet transform (NSCT) with the whale optimization algorithm (WOA). First, the mammography X-ray image was processed by histogram equalization to ensure global image contrast. The processed image was...

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Publicado en:Medical & Biological Engineering & Computing Vol. 57; no. 10; pp. 2245 - 2264
Autores principales: Zhang, Chang-Jiang, Nie, Huan-Huan
Formato: Journal Article
Publicado: Springer Nature Oct2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Oct2019
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      pub: Springer Nature
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        atl: An adaptive enhancement method for breast X-ray images based on the nonsubsampled contourlet transform domain and whale optimization algorithm.
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        au:
          Zhang, Chang-Jiang
          Nie, Huan-Huan
        affil: College of Physics and Electronic Information Engineering, Zhejiang Normal University, 321004, Jinhua, Zhejiang, China
      sug:
        subj:
          Algorithms
          Mammography Methods
          X-Rays
          Female
          Image Processing, Computer Assisted
          Ferrans and Powers Quality of Life Index
          Scales
          Female
      ab: We propose a new method for breast X-ray image adaptive enhancement that combines nonsubsampled contourlet transform (NSCT) with the whale optimization algorithm (WOA). First, the mammography X-ray image was processed by histogram equalization to ensure global image contrast. The processed image was then decomposed into three layers in the NSCT domain. Each layer was each decomposed into two, four, and eight directions. A median filter was used to remove noise in the first and second layers. Then, a special edge filter was adopted to enhance each sub-band image, and two parameters are involved. WOA is used to automatically search the optimal two parameters. Blind image quality index (BIQI) adaptive function was used as an objective function of WOA. Then, inverse NSCT was employed to reconstruct the processed image, generating the final adaptive enhancement image. The digital database for screening mammography (DDSM) was used to verify the performance of the proposed method. Five objective evaluation indexes, including information entropy, average gradient, standard deviation, contrast improvement index (CII), and BIQI, are combined together to construct a new comprehensive index to evaluate the visual quality of the enhanced image. The results show that the proposed method has a good enhancement effect for mammography X-ray images. The overall performance of the proposed method is better than some existing similar methods. Graphical abstract .
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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