Contour Extraction of Drosophila Embryos Based on Conditional Generative Adversarial Nets

Hui Huang, Zhoutao Wang, Y. Gong, Qingzhen Xu
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引用次数: 1

Abstract

High-quality Drosophila embryo images can provide reliable data sources for the research of gene expression and gene interaction. Based on the Drosophila embryo images, a FEMine system is constructed to assist geneticists in quickly mining information for analysis. The extraction of interested Drosophila embryo is an important pretreatment in the FEMine systems. In this paper, taking contour extraction task as image generation task, we proposed a conditional generative adversarial network to generate contour maps of the same size as input images. Based on the Drosophila embryo manual dataset DEDS(Drosophila embryo Dataset)1, for each of the ground-truth, we turn the regions of the interested Drosophila embryo into contours of that. The experiments on DEDS demonstrate that our framework can efficiently extract the contours of the interested Drosophila embryos.
基于条件生成对抗网络的果蝇胚胎轮廓提取
高质量的果蝇胚胎图像可以为基因表达和基因相互作用的研究提供可靠的数据来源。基于果蝇胚胎图像,构建了一个FEMine系统,以帮助遗传学家快速挖掘信息进行分析。感兴趣果蝇胚胎的提取是雌性系统中重要的预处理工作。本文将轮廓提取任务作为图像生成任务,提出了一种条件生成对抗网络来生成与输入图像大小相同的轮廓图。基于果蝇胚胎手册数据集DEDS(Drosophila embryo dataset)1,对于每个ground-truth,我们将感兴趣的果蝇胚胎区域转换为该区域的轮廓。在DEDS上的实验表明,我们的框架可以有效地提取感兴趣的果蝇胚胎的轮廓。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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