Titlebook: Simulation and Synthesis in Medical Imaging; 6th International Wo David Svoboda,Ninon Burgos,Can Zhao Conference proceedings 2021 Springer

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书目名称Simulation and Synthesis in Medical Imaging影响因子(影响力)




书目名称Simulation and Synthesis in Medical Imaging影响因子(影响力)学科排名




书目名称Simulation and Synthesis in Medical Imaging网络公开度




书目名称Simulation and Synthesis in Medical Imaging网络公开度学科排名




书目名称Simulation and Synthesis in Medical Imaging被引频次




书目名称Simulation and Synthesis in Medical Imaging被引频次学科排名




书目名称Simulation and Synthesis in Medical Imaging年度引用




书目名称Simulation and Synthesis in Medical Imaging年度引用学科排名




书目名称Simulation and Synthesis in Medical Imaging读者反馈




书目名称Simulation and Synthesis in Medical Imaging读者反馈学科排名

扔掉掐死你

Joint Image and Label Self-super-Resolutiontput. We evaluated our method with 50 .-weighted brain MR images . down-sampled with 10 automatically generated labels. In comparison to other methods, our method had superior Dice across all labels and competitive metrics on the MR image. Our approach is the first reported method for SSR of paired anisotropic image and label volumes.

Erythropoietin

Inelasticity

MOAN

Cine-MRI Simulation to Evaluate Tumor Tracking parameters and adding noise. The simulator generates a total of 84 Cine-MRI sequences, thus having 12 videos per patient. We validate the simulated versus the real Cine-MRI in terms of tumor motion. Finally, we used the simulator to evaluate the performance of real-time tumor tracking algorithms with this dataset.

Cholecystokinin

Detail Matters: High-Frequency Content for Realistic Synthetic MRI Generation is the scarcity of quality-labelled samples needed for their training. The lack of labelled training data is often addressed by augmentation methods, which aim to synthesise realistic samples with corresponding labels. While the synthesis of realistic samples remains a challenging task, little is k

可行

Mindfulness

Super-Resolution by Latent Space Exploration: Training with Poorly-Aligned Clinical and Micro CT Ima-resolution (LR) and high-resolution (HR) images for training. For obtaining paired LR and HR images in medical imaging, we need to align low and high-resolution data using image registration technology. However, since the hardness of aligning LR and HR images, the aligned LR-HR dataset is always lo

flammable

overrule