论文标题
MISCNN框架的乳腺癌细胞核分割和分析
Nucleus Segmentation and Analysis in Breast Cancer with the MIScnn Framework
论文作者
论文摘要
NUCLS数据集包含乳腺癌中细胞核的220.000多个注释。我们展示了如何使用这些数据创建具有MISCNN框架的多评价者模型来自动化细胞核的分析。对于模型创建，我们使用嵌入管道中的广泛的U-NET方法。该管道还提供了高性能卷积神经网络，几种预处理技术和扩展数据探索。最终模型在评估阶段使用多种指标进行测试，并随后可视化。最后，将结果与NUCLS研究的结果进行比较和解释。作为一个前景，给出了对于在细胞核的情况下对模型的未来发展至关重要的指示。
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.
