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Found 5 papers, 0 papers with code
Tailored Multi-Organ Segmentation with Model Adaptation and Ensemble
Multi-organ segmentation, which identifies and separates different organs in medical images, is a fundamental task in medical image analysis.
Unified Multi-Modal Image Synthesis for Missing Modality Imputation
Besides, we propose a Dynamic Feature Unification Module to integrate information from a varying number of available modalities, which enables the network to be robust to random missing modalities.
DuCN: Dual-children Network for Medical Diagnosis and Similar Case Recommendation towards COVID-19
Our proposed network contains two stages: the first one is a lung region segmentation step and is used to exclude irrelevant factors, and the second is a detection and recommendation stage.
Multi-phase Liver Tumor Segmentation with Spatial Aggregation and Uncertain Region Inpainting
In this work, we propose a novel LiTS method to adequately aggregate multi-phase information and refine uncertain region segmentation.
W-net: Simultaneous segmentation of multi-anatomical retinal structures using a multi-task deep neural network
To further prove the generalization property of the proposed method, we applied the trained model on the DRIONS-DB dataset for OD segmentation and on the MESSIDOR dataset for exudate segmentation.
