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Computational tools for automated histological image analysis and quantification in cardiac tissue

机译:用于自动组织学图像分析和心脏组织定量的计算工具

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Image processing and quantification is a routine and important task across disciplines in biomedical research. Understanding the effects of disease on the tissue and organ level often requires the use of images, however the process of interpreting those images into data which can be tested for significance is often time intensive, tedious and prone to inaccuracy or bias. When working within resource constraints, these different issues often present a trade-off between time invested in analysis and accuracy. To address these issues, we present two novel open source and publically available tools for automated analysis of histological cardiac tissue samples:?Automated Fibrosis Analysis Tool (AFAT) for quantifying fibrosis; and?Macrophage Analysis Tool (MAT) for quantifying infiltrating macrophages.
机译:图像处理和量化是生物医学研究中界定学科的例程和重要任务。了解疾病对组织和器官水平的影响通常需要使用图像,然而将这些图像解释为可以测试的数据的数据通常是时间密集,繁琐的并且容易不准确或偏差。在资源限制范围内工作时,这些不同的问题通常在投资分析和准确性方面的时间之间进行权衡。为解决这些问题,我们提出了两种新颖的开源和公开可用的工具,用于组织学心脏组织样品的自动分析:?用于量化纤维化的自动纤维化分析工具(AWAT);和巨噬细胞分析工具(垫)用于量化浸润巨噬细胞。

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