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Enhancement and denoising method for low-quality MRI, CT images via the sequence decomposition Retinex model, and haze removal algorithm

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Abstract

The visibility and analyzability of MRI and CT images have a great impact on the diagnosis of medical diseases. Therefore, for low-quality MRI and CT images, it is necessary to effectively improve the contrast while suppressing the noise. In this paper, we propose an enhancement and denoising strategy for low-quality medical images based on the sequence decomposition Retinex model and the inverse haze removal approach. To be specific, we first estimate the smoothed illumination and de-noised reflectance in a successive sequence. Then, we apply a color inversion from 0–255 to the estimated illumination, and introduce a haze removal approach based on the dark channel prior to adjust the inverted illumination. Finally, the enhanced image is generated by combining the adjusted illumination and the de-noised reflectance. As a result, improved visibility is obtained from the processed images and inefficient or excessive enhancement is avoided. To verify the reliability of the proposed method, we perform qualitative and quantitative evaluation on five MRI datasets and one CT dataset. Experimental results demonstrate that the proposed method strikes a splendid balance between enhancement and denoising, providing performance superior to that of several state-of-the-art methods.

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Acknowledgements

The authors thank the editor and anonymous reviewers for their commons and suggestions on the manuscripts.

Funding

This work was supported by the National Natural Science Foundation of China (NNSFC) (grant nos. 11772081, 11972106).

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Tianjin University, Tianjin, 300072, People’s Republic of China

    Lei Chen, Chen Tang & Min Xu

  2. State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian, 116024, People’s Republic of China

    Zhenkun Lei

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  1. Lei Chen
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  2. Chen Tang
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  3. Min Xu
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  4. Zhenkun Lei
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Correspondence to Chen Tang.

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Chen, L., Tang, C., Xu, M. et al. Enhancement and denoising method for low-quality MRI, CT images via the sequence decomposition Retinex model, and haze removal algorithm. Med Biol Eng Comput 59, 2433–2448 (2021). https://doi.org/10.1007/s11517-021-02451-6

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  • DOI: https://doi.org/10.1007/s11517-021-02451-6

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