The Network of European Bioimage Analysts (NEUBIAS).
Nikon Imaging Center, University of Heidelberg, Heidelberg, Germany.
EMBO J. 2021 Feb 1;40(3):e105889. doi: 10.15252/embj.2020105889. Epub 2021 Jan 22.
Image data are universal in life sciences research. Their proper handling is not. A significant proportion of image data in research papers show signs of mishandling that undermine their interpretation. We propose that a precise description of the image processing and analysis applied is required to address this problem. A new norm for reporting reproducible image analyses will diminish mishandling, as it will alert co-authors, referees, and journals to aberrant image data processing or, if published nonetheless, it will document it to the reader. To promote this norm, we discuss the effectiveness of this approach and give some step-by-step instructions for publishing reproducible image data processing and analysis workflows.
图像数据在生命科学研究中无处不在。但对其的妥善处理却并非如此。研究论文中的相当一部分图像数据显示出处理不当的迹象,从而影响了对它们的解读。我们认为,需要对所应用的图像处理和分析进行准确描述,以解决这个问题。报告可重现的图像分析的新规范将减少处理不当的情况,因为它会提醒共同作者、评审员和期刊注意异常的图像数据处理,或者,如果已经发表,也会向读者记录下来。为了促进这一规范,我们讨论了这种方法的有效性,并给出了一些逐步的说明,用于发布可重现的图像数据处理和分析工作流程。