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- W4385544612 abstract "Quantitative analysis of hyperpolarized 129 Xe MRI, segmentation of the thoracic cavity, a crucial step that is often the bottleneck in an otherwise fully automated pipeline. This problem is attractive to solve using deep learning methods, but they are limited by their large appetite for manually segmented training data. To this end, we propose a method to automatically synthesize both 129 Xe ventilation MR images and their corresponding thoracic cavity masks using general adversarial networks. This data augmentation technique can accelerate the training of deep learning segmentation models." @default.
- W4385544612 created "2023-08-04" @default.
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- W4385544612 date "2023-08-03" @default.
- W4385544612 modified "2023-09-27" @default.
- W4385544612 title "A general framework of synthesizing 129Xe MRI data for improved segmentation model training" @default.
- W4385544612 doi "https://doi.org/10.58530/2022/1183" @default.
- W4385544612 hasPublicationYear "2023" @default.
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