The NuCLS dataset contains over 220.000 annotations of cell nuclei in breast cancers. We show how to use these data to create a multi-rater model with the MIScnn Framework to automate the analysis of cell nuclei. For the model creation, we use the widespread U-Net approach embedded in a pipeline. This pipeline provides besides the high performance convolution neural network, several preprocessor techniques and a extended data exploration. The final model is tested in the evaluation phase using a wide variety of metrics with a subsequent visualization. Finally, the results are compared and interpreted with the results of the NuCLS study. As an outlook, indications are given which are important for the future development of models in the context of cell nuclei.
翻译：NuCLS 数据集包含超过 220 000 个乳腺癌细胞核的注解。 我们展示了如何使用这些数据来利用MISCnn 框架建立一个多鼠标模型,以自动分析细胞核。 对于模型的创建,我们使用嵌入管道中的广泛的 U-Net 方法。这条管道除了提供高性能神经神经神经网络、若干预处理技术和扩大的数据探索外,还提供其他服务。最后模型在评估阶段使用多种计量进行测试,并随后进行可视化。最后,将结果与 NOCLS 研究的结果进行比较和解释。作为展望,我们给出了对未来细胞核模型开发十分重要的迹象。
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