Member of STM and COPE · Supporting research and publication integrity
Trusted Members of








Identify image issues early, ensure transparency, and protect academic reputation before submission.
Hear from universities and academic publishers using Imagetwin.
Laura Smith, Senior Preflight Coordinator, Rochelle Ritacco, Preflight Editor
Our lab at The Pennsylvania State University works extensively with microscopy images, including fluorescence, confocal, and SEM data in bio-based materials, biomaterials, and regenerative engineering research. ImageTwin helps us screen figures before submission and detect potential duplications across complex datasets. It adds an important layer of quality control and supports our commitment to research integrity prior to publication.
Amir Sheikhi, Associate Professor at Penn State University
Taylor & Francis began using Imagetwin within Dove Medical Press in 2022 as a standalone solution to strengthen image screening. Since then, the platform has been integrated via API into our submission system on selected journals, enabling scalable and automated screening across our workflow. Imagetwin’s duplication detection capabilities, supported by its extensive database, enhance our ability to conduct broader screening and ensure the authenticity of submitted figures. This integration supports efficiency, strengthens confidence in the editorial process, and reinforces our commitment to protecting the integrity and reputation of the research we publish.
Shay O'Neill, Consulting Editor Manager, Taylor & Francis
Imagetwin is an active member of internationally recognized publishing and research ethics organizations. Our work aligns with global standards for research integrity, ethical content handling, and responsible technology use.
Tools designed for graduate schools, research offices, and ethics committees.
Quickly scan large volumes of dissertations, theses, and faculty papers for potential integrity issues
Investigate flagged images with contrast adjustment, keypoint matching, and geometric transformation analysis
Probability scores show the likelihood an image was duplicated, manipulated, plagiarised, or AI-generated
Generate detailed PDF reports summarizing integrity concerns
All data is encrypted and stored securely, ensuring compliance with university privacy standards
Imagetwin makes it easy to incorporate image verification into existing processes with APIs
Let us know, and we are happy to get in touch.
Imagetwin detects:
At Rockefeller University Press, we have conducted in-house image forensic checks for decades, combining expert visual assessment in Photoshop with strong editorial oversight. Imagetwin strengthens this process by identifying image duplications that are difficult or impossible for the human eye to detect, particularly across previously published literature, even from other journals and preprints. Duplication and plagiarism detection capabilities extend our existing integrity checks, much as text screening tools have supported plagiarism detection for years. The visual comparison interface, especially the side-by-side “eyeball” view, makes it straightforward to assess flagged cases efficiently while preserving the critical role of human judgment in editorial decisions.