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DEEP LEARNING-BASED MULTI-SITE, MULTI-PRIMITIVE SEGMENTATION FOR NEPHROPATHOLOGY USING RENAL BIOPSY WHOLE SLIDE IMAGES

机译:基于深度学习的多网站,使用肾活检整个幻灯片图像进行肾病学的多原始分段

摘要

Embodiments discussed herein facilitate segmentation of histological primitives from stained histology of renal biopsies via deep learning and/or training deep learning model(s) to perform such segmentation. One example embodiment is configured to access a first histological image of a renal biopsy comprising a first type of histological primitives, wherein the first histological image is stained with a first type of stain; provide the first histological image to a first deep learning model trained based on the first type of histological primitive and the first type of stain; and receive a first output image from the first deep learning model, wherein the first type of histological primitives is segmented in the first output image.
机译:本文讨论的实施方案促进了通过深度学习和/或训练深层学习模型的肾活检的染色组织学的组织学元素的分割,以进行这种分割。一个示例实施例被配置为进入包含第一类组织学元素的肾活检的第一组织学图像,其中第一组织学图像用第一类​​型的染色染色;将第一组织学图像提供给基于第一类组织学元素和第一类型染色的第一培训的第一深深学习模型;从第一深度学习模型接收第一输出图像,其中第一类型的组织学元素在第一输出图像中被分段。

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