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

Abstract:

: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 .

journal_name

Med Biol Eng Comput

authors

Zhang CJ,Nie HH

doi

10.1007/s11517-019-02022-w

subject

Has Abstract

pub_date

2019-10-01 00:00:00

pages

2245-2263

issue

10

eissn

0140-0118

issn

1741-0444

pii

10.1007/s11517-019-02022-w

journal_volume

57

pub_type

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