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SEGMENTING 3D INTRACELLULAR STRUCTURES IN MICROSCOPY IMAGES USING AN ITERATIVE DEEP LEARNING WORKFLOW THAT INCORPORATES HUMAN CONTRIBUTIONS
SEGMENTING 3D INTRACELLULAR STRUCTURES IN MICROSCOPY IMAGES USING AN ITERATIVE DEEP LEARNING WORKFLOW THAT INCORPORATES HUMAN CONTRIBUTIONS
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机译:使用迭代的深度学习工作流程分割3D细胞内结构,其使用涉及人类贡献的迭代深度学习工作流程
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摘要
A facility for identifying the boundaries of 3-dimensional structures in 3-dimensional images is described. For each of multiple 3-dimensional images, the facility receives results of a first attempt to identify boundaries of structures in the 3-dimensional image, and causes the results of the first attempt to be presented to a person. For each of a number of 3-dimensional images, the facility receives input generated by the person providing feedback on the results of the first attempt. The facility then uses the following to train a deep-learning network to identify boundaries of 3-dimensional structures in 3-dimensional images: at least a portion of the plurality of 3-dimensional images, at least a portion of the received results, and at least a portion of provided feedback.
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