标签繁殖技术对果蝇胚胎阶段的注释

T. Kazmar, E. Kvon, A. Stark, Christoph H. Lampert
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引用次数: 5

摘要

在这项工作中,我们提出了一个系统的自动分类果蝇胚胎的发育阶段。虽然该系统旨在解决生物学研究中的实际问题,但我们相信,它背后的原理不仅对生物学家来说很有趣,而且对计算机视觉研究人员来说也很有趣。主要思想是结合两个正交的信息源:一个是在强不变特征上训练的分类器,这使得它适用于非常不同条件的图像,但也会导致相当嘈杂的预测。另一种是基于更强大的相似性度量的标签传播步骤,但是一次只能在特定的数据子集内保持一致。在我们的生物学设置中,信息源是胚胎图像的形状和染色模式。我们通过实验证明,虽然这两种方法都不能单独使用以获得令人满意的结果,但它们的组合可以实现与人类性能相当的预测质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Drosophila Embryo Stage Annotation Using Label Propagation
In this work we propose a system for automatic classification of Drosophila embryos into developmental stages. While the system is designed to solve an actual problem in biological research, we believe that the principle underlying it is interesting not only for biologists, but also for researchers in computer vision. The main idea is to combine two orthogonal sources of information: one is a classifier trained on strongly invariant features, which makes it applicable to images of very different conditions, but also leads to rather noisy predictions. The other is a label propagation step based on a more powerful similarity measure that however is only consistent within specific subsets of the data at a time. In our biological setup, the information sources are the shape and the staining patterns of embryo images. We show experimentally that while neither of the methods can be used by itself to achieve satisfactory results, their combination achieves prediction quality comparable to human performance.
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