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Texture Pattern-based Bi-directional Projections for Medical Image Super-resolution

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Abstract

The goal of Super-Resolution (SR) is to generate a plausible and visually pleasing High-Resolution (HR) image from a degenerate Low-Resolution (LR) image. High-resolution medical images help improve the accuracy of subsequent operations such as segmentation or remote diagnosis. In this paper, we propose a novel learning-based medical image SR method which directly establishes a bi-directional projection for each texture pattern (texture structures which appear periodically in images) in HR and LR domains. In particular, considering that the feature extraction method should be closely combined with the subsequent steps and the loss of detail is different when different texture patterns degenerate, we propose an auxiliary network to extract features and generate representative texture patterns simultaneously. Then, the textural dictionary is constructed for each texture pattern by introducing texture complexity prior. Hence, the dictionary contains more information when the corresponding texture pattern is complex. Finally, the projections are calculated on these dictionaries with low rank constraint. Extensive experimental results indicate that the proposed method is effectiveness and can deliver higher quality of SR results.

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Data Availability

The raw/processed data required to reproduce these findings cannot be shared at this time as the data also forms part of an ongoing study.

Notes

  1. https://www.siemens-healthineers.com/

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Acknowledgements

This work is supported by the National Natural Science Foundation of China under Grant 61673220, and the Natural Science Research of Jiangsu Higher Education Institutions of China under Grant No. 22KJB520021

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Authors and Affiliations

  1. School of Computer Science and Engineering, Nanjing University of Science and Technology, No. 200 Xiao Ling Wei Street, Nanjing, 210094, Jiangsu, China

    Ying Zhou, Zhichao Zheng & Quansen Sun

  2. School of Computer and Electronic Information/ School of Artificial Intelligence, Nanjing Normal University, No.1 Wenyuan Road Qixia District, Nanjing, 210023, Jiangsu, China

    Zhichao Zheng

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  1. Ying Zhou
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  2. Zhichao Zheng
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  3. Quansen Sun
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Correspondence to Quansen Sun.

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Zhou, Y., Zheng, Z. & Sun, Q. Texture Pattern-based Bi-directional Projections for Medical Image Super-resolution. Mobile Netw Appl (2023). https://doi.org/10.1007/s11036-023-02166-y

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