Strengthening Scientific Integrity: Digital Forensics for Biomedical Research Imaging

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.

Authors

Institutions

Publication Details

Published
2025-07-20
DOI
https://doi.org/10.5753/ctd.2025.9167
Primary Topic
Digital Media Forensic Detection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Strengthening Scientific Integrity: Digital Forensics for Biomedical Research Imaging

Anderson Rocha, João Phillipe Cardenuto, Daniel Moreira
Digital Media Forensic Detection
article

Strengthening Scientific Integrity: Digital Forensics for Biomedical Research Imaging

Anderson Rocha, João Phillipe Cardenuto, Daniel Moreira
article en

Abstract

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.

Universidade Estadual de Campinas (UNICAMP) (BR), Loyola University Chicago (US), Hospital de Clínicas da Unicamp (BR)
Openalex Percentile: Top 78%
Digital Media Forensic Detection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Strengthening Scientific Integrity: Digital Forensics for Biomedical Research Imaging — Anderson Rocha, João Phillipe Cardenuto, et al. · (2025) | TGRS Research Map | TGRS