This research demonstrates novel techniques for detecting image manipulation in biomedical publications, indicating key advances in digital forensics.
To fight against the increasing misconduct cases in science, this Ph.D. research confronted the challenge of scientific integrity with a pioneering investigation into digital forensic analysis specifically tailored for biomedical images. This work conducted extensive research into key manipulation types – copy-move forgery, image reuse, and AI-generated content – developing novel, fully explainable, and auditable computational detection methods for each. In a commitment to transparency and to promote research to the area, these techniques are provided as open-source resources. Besides the isolated techniques for each type of image forged, a central contribution is the development of an end-to-end system, created through collaboration with international forensic experts and the U.S. Office of Research Integrity (ORI). This system automates the analysis of scientific publications, starting from PDF documents and ending by identifying figures with potential integrity concerns.
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Cardenuto et al. (2025) studied this question.
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