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Connection

Yuming Jiang to Image Processing, Computer-Assisted

This is a "connection" page, showing publications Yuming Jiang has written about Image Processing, Computer-Assisted.
  1. Jiang Y, Chen C, Xie J, Wang W, Zha X, Lv W, Chen H, Hu Y, Li T, Yu J, Zhou Z, Xu Y, Li G. Radiomics signature of computed tomography imaging for prediction of survival and chemotherapeutic benefits in gastric cancer. EBioMedicine. 2018 Oct; 36:171-182.
    View in: PubMed
    Score: 0.130
  2. Zhang Y, Li L, Wang J, Yang X, Zhou H, He J, Xie Y, Jiang Y, Sun W, Zhang X, Zhou G, Zhang Z. Texture-preserving diffusion model for CBCT-to-CT synthesis. Med Image Anal. 2025 Jan; 99:103362.
    View in: PubMed
    Score: 0.050
  3. Zhou Z, Jiang Y, Sun Z, Zhang T, Feng W, Li G, Li R, Xing L. Virtual multiplexed immunofluorescence staining from non-antibody-stained fluorescence imaging for gastric cancer prognosis. EBioMedicine. 2024 Sep; 107:105287.
    View in: PubMed
    Score: 0.049
  4. Liu L, Fan X, Liu H, Zhang C, Kong W, Dai J, Jiang Y, Xie Y, Liang X. QUIZ: An arbitrary volumetric point matching method for medical image registration. Comput Med Imaging Graph. 2024 Mar; 112:102336.
    View in: PubMed
    Score: 0.047
  5. He W, Zhang C, Dai J, Liu L, Wang T, Liu X, Jiang Y, Li N, Xiong J, Wang L, Xie Y, Liang X. A statistical deformation model-based data augmentation method for volumetric medical image segmentation. Med Image Anal. 2024 Jan; 91:102984.
    View in: PubMed
    Score: 0.046
  6. Zhu Y, Zhao H, Wang T, Deng L, Yang Y, Jiang Y, Li N, Chan Y, Dai J, Zhang C, Li Y, Xie Y, Liang X. Sinogram domain metal artifact correction of CT via deep learning. Comput Biol Med. 2023 Mar; 155:106710.
    View in: PubMed
    Score: 0.044
  7. Liang X, Dai J, Zhou X, Liu L, Zhang C, Jiang Y, Li N, Niu T, Xie Y, Dai Z, Wang X. An Unsupervised Learning-Based Regional Deformable Model for Automated Multi-Organ Contour Propagation. J Digit Imaging. 2023 Jun; 36(3):923-931.
    View in: PubMed
    Score: 0.044
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.