Document Type
Article
Publication Date
10-31-2022
Publication Title
Scientific Reports
Volume
12
Issue
18306
Pages
1-15
Publisher Name
Nature Research
Abstract
A great deal of the images found in scientific publications are retouched, reused, or composed to enhance the quality of the presentation. In most instances, these edits are benign and help the reader better understand the material in a paper. However, some edits are instances of scientific misconduct and undermine the integrity of the presented research. Determining the legitimacy of edits made to scientific images is an open problem that no current technology can perform satisfactorily in a fully automated fashion. It thus remains up to human experts to inspect images as part of the peer-review process. Nonetheless, image analysis technologies promise to become helpful to experts to perform such an essential yet arduous task. Therefore, we introduce SILA, a system that makes image analysis tools available to reviewers and editors in a principled way. Further, SILA is the first human-in-the-loop end-to-end system that starts by processing article PDF files, performs image manipulation detection on the automatically extracted figures, and ends with image provenance graphs expressing the relationships between the images in question, to explain potential problems. To assess its efficacy, we introduce a dataset of scientific papers from around the globe containing annotated image manipulations and inadvertent reuse, which can serve as a benchmark for the problem at hand. Qualitative and quantitative results of the system are described using this dataset.
Recommended Citation
Moreira, Daniel; Cardenuto, João Phillipe; Shao, Ruiting; Baireddy, Sriram; Cozzolino, Davide; Gragnaniello, Diego; Abd-Almageed, Wael; Bestagini, Paolo; Tubaro, Stefano; Rocha, Anderson; Scheirer, Walter; Verdoliva, Luisa; and Delp, Edward. SILA: A System for Scientific Image Analysis. Scientific Reports, 12, 18306: 1-15, 2022. Retrieved from Loyola eCommons, Computer Science: Faculty Publications and Other Works, http://dx.doi.org/10.1038/s41598-022-21535-3
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright Statement
(c) The Authors, 2022.
Comments
Author Posting (c) The Authors, 2022. This article is posted here by permission of Nature Research for personal use, not for redistribution. The article was published in Scientific Reports, VOL12, 31 October 2022, http://dx.doi.org/10.1038/s41598-022-21535-3