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    • Frequency adaptation and feature transformation network for medical image segmentation

    • A new breakthrough has been made in the field of medical image lesion segmentation, and relevant experts have constructed a segmentation network that integrates frequency adaptation and feature transformation. This network significantly improves segmentation accuracy by dynamically balancing high and low frequency components and optimizing downsampling strategies, providing strong support for precise clinical diagnosis and treatment formulation.
    • Vol. 31, Issue 1, Pages: 303-319(2026)   

      Received:20 March 2025

      Revised:2025-07-12

      Accepted:01 August 2025

      Published:16 January 2026

    • DOI: 10.11834/jig.250100     

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  • Zhu Zhiqin, Sun Mengwei, Qi Guanqiu, Li Yuanyuan, Yang Mengjie, Cheng Jun, Liu Yu. 2026. Frequency adaptation and feature transformation network for medical image segmentation. Journal of Image and Graphics, 31(1):0303-0319 DOI: 10.11834/jig.250100.
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相关作者

Zhu Zhiqin 重庆邮电大学自动化学院
Sun Mengwei 重庆邮电大学自动化学院
Qi Guanqiu 纽约州立大学布法罗州立大学,布法罗 NY
Li Yuanyun 重庆邮电大学自动化学院
Yang Mengjie 盛云科技有限公司
Cheng Jun 中国科学院先进技术研究院
liu Yu 合肥工业大学生物医学工程学院
Xu Wangwang 合肥综合性国家科学中心人工智能研究院;合肥工业大学计算机与信息学院

相关机构

Computer Information Systems Department,State University of New York at Buffalo State
Institute of Artificial Intelligence, Hefei Comprehensive National Science Center
School of Computer Science and Information Engineering, Hefei University of Technology
Anhui Water Conservancy and Electric Power Technical College
The First Affiliated Hospital of Anhui Medical University
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