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Unlocking efficient gigapixel whole slide pathological image compression via diagnostic-aware attention guidance

  • 1.

    Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China

  • 2.

    University of Chinese Academy of Science, Beijing 101400, China

  • 3.

    State Key Laboratory of Biomedical Imaging Science and System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China

  • 4.

    National Innovation Center for Advanced Medical Devices, Shenzhen 518055, China

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  • Corresponding author: wj.qin@siat.ac.cn
  • Received Date:  December 29, 2025
    Accepted Date:  July 06, 2026
    Published Online:  July 09, 2026
The Innovation Informatics  https://doi.org/10.59717/j.xinn-inform.2026.100053  |  Cite this article
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    [3] Artuğer F. and Özkaynak F. (2023). Chaotic quantization based JPEG for effective compression of whole slide images. Vis. Comput. 39:5609−5623. DOI:10.1007/s00371-022-02684-y

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    [7] TIGER: Grand Challenge (2022). https://tiger.grandchallenge.org (Accessed Nov-2022

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  • Cite this article:

    Liu X., Chen F., He J., et al. (2026). Unlocking efficient gigapixel whole slide pathological image compression via diagnostic-aware attention guidance. The Innovation Informatics 2:100053. https://doi.org/10.59717/j.xinn-inform.2026.100053
    Liu X., Chen F., He J., et al. (2026). Unlocking efficient gigapixel whole slide pathological image compression via diagnostic-aware attention guidance. The Innovation Informatics 2:100053. https://doi.org/10.59717/j.xinn-inform.2026.100053

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