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- W4380451225 abstract "Creating regions of interest (ROIs) from 3D image data, like that from CT or MRI scans, is known as medical image segmentation. The main goal of segmenting this data is to determine which anatomical components are required for a particular inquiry. One of the key benefits of medical image segmentation is that it allows for a more accurate In order to separate brain tumors on the Brats2019 dataset, we will use Mean Teacher, a straightforward method for semi-supervised learning, with the 3D-Unet backbone network." @default.
- W4380451225 created "2023-06-14" @default.
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- W4380451225 date "2023-01-01" @default.
- W4380451225 modified "2023-09-27" @default.
- W4380451225 title "Semi-Supervised Medical Image Segmentation on Data from Different Distributions" @default.
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- W4380451225 doi "https://doi.org/10.1007/978-981-99-0769-4_11" @default.
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