Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
661-04-001 ISMRM Abstract

Cross-modal Brain Connectivity Prediction with Topology-aware Signed Graph Diffusion Model

Primary: Analysis Methods - Classification and Prediction
Secondary: Brain Function and fMRI - Functional Connectivity
661-04-001 · AI-Based Analysis in MR Imaging · Thursday, 14 May, 2:35 PM–3:30 PM · Digital Posters Row B
Keywords: Brain Connectivity Structural Connectivity Brain Functional Network Artificial Intelligence (AI) Deep Learning Cross-modal Brain Connectivity Prediction
Accepted
Xinrui Chen 1, Yin Huang, Geng Chen1
1Northwestern Polytechnical University, Xi'An, China
Presenting Author: Xinrui Chen

Synopsis

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References

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8. Egghe, Leo, and Loet Leydesdorff. "The relation between Pearson's correlation coefficient r and Salton's cosine measure." Journal of the American Society for information Science and Technology 60.5 (2009): 1027-1036. https://doi.org/10.1002/asi.21009 [doi]
9. Zhang, Lu, et al. "Predicting brain structural network using functional connectivity." Medical image analysis 79 (2022): 102463. https://doi.org/10.1016/j.media.2022.102463 [doi]
10. Demirbilek, Oytun, Tingying Peng, and Alaa Bessadok. "Graph Residual Noise Learner Network for Brain Connectivity Graph Prediction." International Workshop on Graphs in Biomedical Image Analysis. Cham: Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-83243-7_3 [doi]
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http://echo.ismrm.org/p/ISMRM2026/661-04-001