We created a custom pipeline (histo-fetch) to efficiently extract random patches and labels from pathology whole slide images (WSIs) for input to a neural network on-the-fly. We prefetch these patches as needed during network training, avoiding the need for WSI preparation such as chopping/tiling. We demonstrate the utility of this pipeline to perform artificial stain transfer and image generation using the popular networks CycleGAN and ProGAN, respectively.

中文翻译：

---

Histo-fetch-动态处理千兆像素的整个幻灯片图像简化并加速了神经网络训练

我们创建了一个自定义管道（组织提取），以从病理学完整幻灯片图像（WSI）中高效提取随机斑块和标签，以实时输入到神经网络。我们会在网络培训期间根据需要预取这些修补程序，从而避免了WSI准备工作（例如斩波/平铺）。我们演示了该管道的实用程序，分别使用流行的网络CycleGAN和ProGAN执行人工污渍转移和图像生成。