生命科学

细胞分类和计数

深度学习式算法根据独特的特征分类细胞类型。

Cognex Cell Classification and Counting

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细胞分类和计数是临床诊断中的关键任务(例如血涂片或有丝分裂计数)。很多流程需要准确的初始细胞计数来标准化其基线输入和测量结果。因为细胞的外观可能不同,所以机器视觉有时难以准确地将它们与混乱的背景或伪影区分开来。机器视觉也很难将那些靠在一起的细胞识别为独立细胞。

The Cognex ViDi Blue-Locate tool accurately identifies cells by learning from annotated images of microscopic slides. The tool generalizes the normal appearance of cells based on their size, shape, and surface features as well as variable features. Self-learning algorithms learn to differentiate between intact and damaged cells (for example, those which carry a malaria virus), even on noisy backgrounds, and provide a reliable count. The ViDi Green-Classify tool learns to sort different types of cells, classifying them by unique characteristics such as size and shape.

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