Reversible contrast enhancement for medical images with background segmentation

Hao Tian Wu, Qi Huang, Yiu Ming CHEUNG*, Lingling Xu, Shaohua Tang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Contrast enhancement (CE) of medical images is helpful to bring out the unclear content in the interested regions. Recently, reversible CE has been proposed so that the original version of a contrast-changed image can be exactly recovered. This property can be used to save storage space or facilitate the archiving system. To enhance the regions of interest (ROI) without introducing visual distortions, the technique of image segmentation (e.g. using Otsu's method) has been used to obtain the background before conducting the CE process. To segment the ROI more accurately, an interactive algorithm called GrabCut is employed in the proposed scheme. In addition, a new preprocessing strategy is adopted to preserve the image quality through the CE process. Consequently, the content in the selected regions can be better brought out while the reversibility of the CE process is achieved. The experimental results on 30 chest radiograph images and 20 magnetic resonance images have demonstrated the efficacy of the proposed scheme for reversible CE. The evaluation results are provided to show the better performances of the proposed method in achieving CE effects and preserving image quality.

Original languageEnglish
Pages (from-to)327-336
Number of pages10
JournalIET Image Processing
Volume14
Issue number2
DOIs
Publication statusPublished - 7 Feb 2020

Scopus Subject Areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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