Statistical Forensics

Image Manipulation

General Information

Image manipulation is the purposeful transformation or alteration of an image using various methods and techniques to achieve desired results. Image manipulation has been a growing issue in the world of research. In fact, since 2007, 68% of open cases of research misconduct involved falsified or manipulated images (Gilbert, 2009). There are many types of ways one can manipulate images, however, the most common are splicing (lanes or features in images have been removed or rearranged) and extreme contrast adjustment. Though these two do not affect the results or data in a paper, these are still not good because it’s still an alteration to the real images. Other errors include: duplication of images in a multi-panel figure, erasing/editing parts of images, and enhancing contrast/color on a specific feature within a figure. These manipulated images usually come from cameras, blots (shows protein expression in an experimental sample), or gels (shows DNA or RNA expression in an experimental sample). 

Although manipulated images could extremely alter the results or one’s possibility of publication, some journals that detect manipulation will ask the authors to provide original images and explanations for slight manipulations. If the authors are unable to do that, then one can suspect scientific and research misconduct. To combat image manipulation, journals can enforce strict policies and establish processes for reviewing images in accepted manuscripts (ISMTE, 2017). To read more about the techniques used to combat image manipulation, please check out our ‘Guidelines and Testing for Image Manipulation’ page. 

Here are resources on the phenomenon:

Aldhous, P. & Reich, E.S. (2009).Further doubts over stem cell images. NewScientist, 203(2720), 12.

Alleged image fraud: Research misconduct? Fabrication? Falsification? Unintentional and inadvertent mistake? Coincidental similarity?. Shigeaki Kato laboratory : Institute of Molecular and Cellular Biosciences.

Amakoh, K. (2020). Five things every researcher should know about image manipulation. Elsevier.

Anderson, C. (1994). Easy-to-alter digital images raise fears of tampering. Science, 263(5145), 317-318.

Bik, E. M., Casadevall, A., & Fang, F. C. The Prevalence of Inappropriate Image Duplication in Biomedical Research Publications. MBio, 7(3).

Couzin-Frankel, J. (2016).Bringing image manipulation to light. Science Magazine.

Davis, P. (2016). Image manipulation: cleaning up the scholarly record. The Scholarly Kitchen.

Davey, M. & Kirchgaessner, S. Surgisphere: mass audit of papers linked to firm behind hydroxychloroquine Lancet study scandal. The Guardian.

Gilbert, N. (2009). Science journals crack down on image manipulation. Nature.

Huang, T.S. & Aizawa, K. (1993). Image processing: some challenging problems. Proceedings of the National Academy of Sciences of the United States of America, 90(21), 9766-9769.

Image Manipulation. Committee on Publication Ethics.

image manipulation – Retraction Watch

McCook, A. (2016). Don’t trust an image in a scientific paper? Manipulation detective’s company wants to help. Retraction Watch.

Nature Publishing Group (2006). Appreciating data: warts, wrinkles and all. Nature Cell Biology, 8(3), 203.

Neistadt, L. E. Image Manipulation. Council of Science Editors, Annual Meeting Reports. 

Noorden, R.V. (2015). The image detective who roots out manuscript flaws. Nature.

Parrish, D., Noonan, B. (2009). Image Manipulation as Research Misconduct. Sci Eng Ethics 15, 161–167.

Pearson, H. (2005). Image manipulation: CSI: cell biology. Nature, 434, 952-953.

Pettersson, Rune. (2002). Image Manipulation. Media and Education.

Rossner, M. (2007). Hwang case review committee misses the mark. The Journal of Cell Biology, 176(2), 131.

White, C. (2007). Software makes it easier for journals to spot image manipulation. BMJ: British Medical Journal, 334(7594), 607.

Zelip, B. (2013). Digital image manipulation and scientific publishing The Scholarly Commons.