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Found 3 papers, 1 papers with code
Constraint-Based Model in Multimodal Learning to Improve Ventricular Arrhythmia Prediction
Both fusion models achieved better scores than the single-modality models, where the average Sensitivity and F1 score are 62. 8% $\pm$ 10. 1; 52. 1% $\pm$ 6. 5 for the clinical data modality and 62. 9% $\pm$ 6. 3; 60. 7% $\pm$ 5. 3 for the medical images modality.
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation
The aim was to automatically perform unilateral VS and bilateral cochlea segmentation on hrT2 as provided in the testing set (N=137).
Cardiac Segmentation on Late Gadolinium Enhancement MRI: A Benchmark Study from Multi-Sequence Cardiac MR Segmentation Challenge
In addition, the paired MS-CMR images could enable algorithms to combine the complementary information from the other sequences for the segmentation of LGE CMR.
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