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AUTOMATED IMAGE ANALYSIS TO ASSESS REPRODUCTIVE POTENTIAL OF HUMAN OOCYTES AND PRONUCLEAR EMBRYOS

机译:自动化图像分析以评估人类卵母细胞和原代胚胎的生殖潜能

摘要

A computer system automatically converts a set of training images of cells (e.g., oocytes or pronuclear embryos) and related outcome metadata into a description document by extracting features (e.g., cytoplasm features) from the pixel values of the training images that describe the cells and associating the extracted features with the outcome metadata. Based on the description document, the system automatically computes a decision model that can be used to predict outcomes of new cells. To predict outcomes of new cells, a computer system automatically extracts features from images that describe the new cells and predicts one or more outcomes by applying the decision model. The features extracted from the images that describe the new cells correspond to features selected for inclusion in the decision model, and are calculated in the same way as the corresponding features extracted from the training images.
机译:计算机系统通过从描述细胞和细胞的训练图像的像素值中提取特征(例如细胞质特征)来自动将一组细胞(例如卵母细胞或原核胚胎)的训练图像和相关结果元数据转换为描述文档。将提取的特征与结果元数据相关联。基于描述文档,系统会自动计算决策模型,该模型可用于预测新细胞的结果。为了预测新细胞的结果,计算机系统自动从描述新细胞的图像中提取特征,并通过应用决策模型预测一个或多个结果。从描述新单元的图像中提取的特征对应于选择用于决策模型中的特征,并以与从训练图像中提取的相应特征相同的方式计算。

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