Author: Kim

Imagetwin Integrates with Wiley’s Research Exchange to Strengthen Image Integrity at Scale

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We are proud to announce that Imagetwin has been integrated into Research Exchange, Wiley’s research publishing platform. Wiley is a global leader in authoritative content and research intelligence for the advancement of scientific discovery, innovation and learning. The integration brings AI-powered image integrity screening to the 25+ research integrity checks already embedded in Research Exchange, enabling editors and integrity specialists to identify potentially manipulated or fraudulent images before publication.

First, a Pilot Proved the Need

Before full rollout, Wiley ran a pilot across multiple journals. The results were clear: Imagetwin detected more than 3x as many image integrity issues as human reviewers alone, flagging manuscripts with concerns that would have otherwise been missed.

Based on those results, Wiley is now rolling out Imagetwin strategically across its journal portfolio, prioritizing disciplines where image integrity risks are most acute: life sciences, biomedical research, and materials science.

How the Integration Works

When a manuscript is submitted to a participating Wiley journal, Imagetwin automatically analyzes each image and flags potential concerns directly within the Research Exchange interface. Editors and research integrity specialists receive a clear, actionable report at key stages of the peer review journey, allowing them to investigate flagged images before publication without disrupting existing workflows.

Why This Matters

Research Exchange is used by more than 1,500 journals published by Wiley and its partners, as well as third-party publishers. At that scale, protecting the integrity of the scientific record requires more than manual review. As Sam Parker, Wiley’s Director of Integrity Platforms, shares:

“Research integrity is a foundational part of Research Exchange, and we are continuously evolving and investing in this technology as the threat landscape evolves. AI-generated and manipulated images that are fraudulently passed off as scientific evidence present a serious risk to the credibility of published research. With this integration, we’re giving our editorial teams the tools they need to proactively catch these issues before they reach publication.”

Patrick Starke, Imagetwin Co-Founder & CEO, supports that statement:

“We’re happy to help advance Wiley’s commitment to research integrity. Integrating Imagetwin into their submission workflow means journals can now, with greater precision, catch image plagiarism, manipulation, duplication, and AI-generated content before publication, which protects the scientific record at scale, and that’s what matters today.”

About Wiley

Wiley (NYSE: WLY) is a global leader in authoritative content and research intelligence for the advancement of scientific discovery, innovation, and learning.  With more than 200 years at the center of the scholarly ecosystem, Wiley combines trusted publishing heritage with AI-powered platforms to transform how knowledge is discovered, accessed, and applied. From individual researchers and students to Fortune 500 R&D teams, Wiley enables the transformation of scientific breakthroughs into real-world impact. From knowledge to impact—Wiley is redefining what’s possible in science and learning.

Visit Wiley at Wiley.com and Investors.Wiley.com. Follow us on Facebook, X,LinkedIn and Instagram.

Frequently asked questions

Yes. Imagetwin is trusted by some of the world’s largest academic publishers, including Wiley, Karger, Sage, and the American Society for Microbiology (ASM). Wiley integrated Imagetwin into Research Exchange, its platform used by more than 1,500 journals, making it one of the largest publisher deployments of AI-powered image integrity screening to date.

Yes. Imagetwin integrates directly into publisher workflows, including Wiley’s Research Exchange. When a manuscript is submitted, Imagetwin automatically screens images and delivers results within the existing editorial interface, no separate login or disrupted workflow required. Integration with additional submission systems is also available.

Imagetwin is integrated into active screening workflows at major publishers including Wiley, Karger, and Sage, and is used by research integrity teams across institutions and universities globally. In a pilot at ASM, Imagetwin flagged image integrity concerns in around 15% of accepted manuscripts, demonstrating real-world detection at scale. Imagetwin is a leading tool in scientific image integrity; Imagetwin differentiates on cross-publication duplicate detection, publisher workflow integration, and per-paper pricing.

WCRI 2026: The World Conference on Research Integrity in Vancouver

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About WCRI

The World Conference on Research Integrity (WCRI) is one of the leading global forums for advancing responsible research. It unites scientists, publishers, institutions, and policymakers who work to strengthen trust, ethics, and accountability in science. WCRI Conference 2026 will focus on three major themes: Artificial Intelligence, Research Security, and Indigenous Knowledge Systems.

WCRI 2026 Themes

Each edition of the World Conference on Research Integrity focuses on key issues that shape how science evolves. The 2026 conference highlights the following:

Artificial Intelligence and Integrity in Scientific Research

AI now plays a central role in how research is created, verified, and shared. It can expose image or data manipulation that might otherwise go unnoticed, exactly what drives Imagetwin’s mission. At the same time, AI also introduces new risks: fabricated results, biased outputs, and unethical use of generative tools. The conference will explore both sides of this shift – how to use AI responsibly while keeping human judgment and transparency at the heart of science.

Research Security and Openness

Modern research depends on collaboration, but it also faces growing security challenges. Governments and institutions must protect sensitive data, intellectual property, and national interests without limiting the open exchange that fuels discovery. WCRI 2026 will focus on this balance: how to keep science transparent and trustworthy while addressing issues such as restricted partnerships, data access, and foreign influence.

Indigenous Knowledge and Ethical Research

This theme highlights the importance of Indigenous perspectives in global research ethics. It calls for genuine engagement with Indigenous ways of knowing and for a deeper respect for community-based research practices. By bringing these voices into the conversation, WCRI 2026 broadens what integrity means: compliance with global standards, cultural awareness, respect, and shared responsibility in how knowledge is created.

Imagetwin at WCRI 2026

Imagetwin will exhibit at the 9th World Conference on Research Integrity in Vancouver, Canada. WCRI’s mission aligns closely with ours: to promote transparency, accountability, and trust in scientific research.

Our AI-driven technology helps researchers, publishers, and institutions detect image duplication, plagiarism, manipulation, and AI-image fabrication before publication. We help protect research credibility and uphold the ethical standards that WCRI stands for by making image verification fast and reliable

We look forward to joining this global conversation on responsible and ethical research, since it will give our team a chance to connect with integrity leaders, exchange insights, and explore how technology can preserve trust in science. 

Visit us at our booth at WCRI 2026 to discuss potential collaborations to support research integrity worldwide.

WCRI Sign Up & Schedule

The 9th World Conference on Research Integrity (WCRI 2026) will take place from May 3–6, 2026, at The Westin Bayshore Hotel in Vancouver, British Columbia, Canada. It is open to researchers, institutions, and policymakers worldwide. 

For more information, visit the official WCRI Canada website for updates on registration, travel, and the full schedule.

About Imagetwin

Imagetwin uses artificial intelligence to verify the integrity of scientific images. Our platform helps publishers, universities, institutions, researchers detect image integrity issues, prevent fraud, and protect scientific credibility at scale. With a mission to make research more transparent and trustworthy, Imagetwin partners with the global scientific community to ensure that published findings reflect genuine, reproducible work. 

If you’d like to learn how Imagetwin supports research integrity or explore potential collaboration, reach out to our team.

Frequently asked questions

Imagetwin includes automated AI-generated image detection as part of its standard screening. When a manuscript is submitted through an integrated platform such as ScholarOne, Wiley’s Research Exchange, or Editorial Manager, Imagetwin flags figures that show signs of AI fabrication alongside checks for duplication, manipulation, and plagiarism. As generative AI tools become more accessible, this type of automated detection at submission is increasingly essential for maintaining the credibility of published research.

Imagetwin analyzes images for manipulation automatically, covering splice detection, copy-paste forgeries, and cross-publication reuse. For Western blots specifically, it produces a color-coded overlay highlighting suspicious regions, with a false positive rate of 1.7%. For manual review, signals to watch for include images that look suspiciously similar in texture or lighting, low-resolution JPEGs where originals should be high quality, and labels or text obscuring image corners. Automated screening with Imagetwin catches what manual review misses, particularly at scale.

The most frequently detected issues are Western blot splicing (vertical or horizontal cuts that combine bands from different experiments), copy-paste duplication within or across figures, microscopy images reused across multiple papers or disease models, and figures taken from unrelated publications and relabeled. AI-generated figures are an emerging category. In a Radboud university medical center investigation of 608 pre-clinical stroke research papers, approximately 40% of articles contained image-related concerns, predominantly duplicated Western blot panels.

Next Level Western Blot Duplicate Detection

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Western Blots are among the most difficult scientific images to analyse for duplication. They often lack distinctive texture or structure, and many look strikingly similar to one another, which can result in a high false positive rate. Our current detection system performs well, but feedback from researchers and editors showed us that some especially challenging cases were slipping through.

Over the past months, our team has been building a stronger system designed specifically to handle these edge cases, and the results are a major step forward.

How We Improved Western Blot Detection

To improve detection, we analysed thousands of Western Blot duplicates identified on PubPeer. These real-world cases helped us understand recurring patterns and highlighted situations where conventional algorithms struggled.

From this foundation, we worked closely with research integrity experts to assemble a large, curated dataset of Western Blot duplicates. This became the basis for training a new machine learning model, purpose-built for this image type.

Key advances in the new system include:

  • Specialised training corpus
    Thousands of confirmed duplicates curated with expert input
  • Next-generation detection model
    Optimised to capture subtle similarities that generic approaches miss
  • Robustness to transformations
    Tested against common transformations such as rotation, scaling, contrast or colour shifts, quality loss, and flipping. These are all areas where the new model shows far stronger performance

What This Means for Users

With this release, duplicate detection between Western blot images has become substantially more accurate, achieving 90% accuracy on 443 verified duplicates collected from PubPeer. Many of the most challenging cases that previously went undetected are now flagged correctly. This reduces the risk of false negatives while giving researchers, editors, and institutions greater confidence in their results.

To demonstrate the impact of this upgrade, we tested the new model against some of the most difficult Western Blot cases shared by researchers and editors, some examples below: 

This means researchers, editors, and institutions can work with greater confidence that duplications will be caught, even in the toughest cases.

Looking Ahead

What we developed is not just a model for Western Blots. We have created a new duplicate detection technology that can be adapted to other use cases. Next, we will extend from duplicate detection between Western Blot images to duplicate detection within single Western Blot subimages. Then, over the coming months, we will roll out the new technology to flow cytometry images, microscopy images, and graphs, strengthening duplicate detection across an even broader range of figures.

By listening to feedback and analyzing real-world cases, we are building ever-stronger tools to support the research community. Western Blot detection is just the latest step in this process, and more improvements are already on the way.

Frequently asked questions

Imagetwin’s manipulation detection model identifies vertical splices, horizontal splices, and copy-paste forgeries in Western blot images. Suspicious regions are highlighted in a color-coded overlay directly in the interface, with brighter areas indicating higher concern. The current false positive rate is 1.7%, and detection rate on splices improved by 14 percentage points with the latest model update.

Both tools detect Western blot manipulation. Imagetwin’s latest model covers vertical splices, horizontal splices, and copy-paste forgeries under a unified detection framework, with a 1.7% false positive rate. Beyond Western blots, Imagetwin also screens for cross-publication image plagiarism against a database of 160M+ published figures, detects AI-generated images, and integrates directly into publisher workflows including ScholarOne and Wiley’s Research Exchange. For publishers and institutions that need both manipulation detection and cross-publication screening in one tool, Imagetwin covers both.

Imagetwin detects manipulation across several categories: splicing (vertical and horizontal cuts), copy-paste forgeries, duplication within and across publications, and AI-generated figures. Western blot detection is currently the most developed, with expansion underway to microscopy images, FACS plots, and light photography. Detection is available via the web application and API.

Imagetwin Expands Reach with Image Integrity Checks in Signals Platform

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We’re pleased to share that Imagetwin’s image analysis technology is now powering integrity checks within Signals Manuscript Checks, a leading platform used by publishers to evaluate submissions at scale. The integration enables publishers to automatically detect image duplication, plagiarism, manipulation, and AI-generated figures directly within their existing editorial workflows.

“”Research integrity shouldn’t require editors and publishers to juggle multiple tools and platforms. Our partnership with Imagetwin means our publisher users can now conduct Imagetwin’s image analysis alongside Signals Manuscript Checks—automatically and seamlessly within their existing editorial systems. Imagetwin are leaders in image integrity detection, and we’re excited to bring their capabilities directly into the Signals platform.””

— Tiago Barros, Signals Co-Founder

The volume and complexity of manuscript submissions continue to rise, bringing with them an increased risk of integrity issues that threaten publisher reputation. While editorial teams have long relied on fragmented tools to cover different aspects of review, this can slow down workflows and leave gaps in screening.

Our collaboration with Signals addresses that challenge by bringing image-based analysis into one consolidated system. Publishers can now:

  • Combine Imagetwin’s image integrity analysis with Signals’ author, reference, and full-text checks in a single platform

  • Flag issues such as duplication, plagiarism, manipulation, or AI generation, automatically, and early in the review process

  • Access image checks seamlessly through ScholarOne, Editorial Manager, or Direct Upload

Publishers are already seeing the benefits of a unified approach. Chad McCormick, Director of Research Integrity at FASEB, shared:

“Research integrity and editorial efficiency are priorities for FASEB. Having both evaluations in one place helps us quickly identify any issues so that we can focus on high-quality research.”

Available Now

Image integrity checks powered by Imagetwin are now available to publishers using Signals Manuscript Checks, including those integrated with ScholarOne and Editorial Manager.

This collaboration reflects a broader shift in scholarly publishing: image integrity is no longer a nice-to-have. It’s essential for protecting research quality and preserving trust in scientific communication.

About Signals

Signals is a comprehensive manuscript analysis platform designed to help publishers detect issues and evaluate submissions with greater accuracy and efficiency. By uniting author, reference, and content checks in one solution, Signals streamlines editorial workflows, reduces manual effort, and enhances decision-making across the publication process.

Frequently asked questions

Imagetwin is used by major academic publishers including Wiley, Karger, Sage, ASM, and FASEB, and is integrated into platforms serving thousands of journals globally. It powers image integrity checks within Signals Manuscript Checks, ScholarOne Manuscripts, Wiley’s Research Exchange, Editorial Manager, CACTUS’s Paperpal Preflight, and Rivyr. Publishers described by Signals co-founder Tiago Barros as already seeing benefits include FASEB, whose Director of Research Integrity confirmed the value of having image and manuscript checks unified in one platform.

Yes. Imagetwin is available within Editorial Manager through integrations with both Signals Manuscript Checks and Rivyr. Publishers using Editorial Manager can run automated image integrity checks covering duplication, manipulation, plagiarism, and AI-generated figures as part of their standard submission workflow, without switching platforms or adding manual steps.

Imagetwin is the leading image integrity tool for both systems. It integrates with ScholarOne via its partnership with Silverchair, and with Editorial Manager via Signals and Rivyr. It screens figures against a database of 160M+ published scientific images, achieves 90% accuracy on Western blot duplicate detection, and runs at a 1.7% false positive rate on manipulation detection. It is trusted by Wiley, Karger, Sage, ASM, and FASEB, and is priced per paper rather than per sub-image.

Imagetwin Powers Image Integrity Checks in Integra’s EditorialPilot

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We’re excited to announce that Imagetwin has been integrated into Integra’s EditorialPilot, an all-in-one AI-powered manuscript screening platform. This partnership makes it easier than ever for publishers to check image integrity at scale, alongside the 40+ other automated checks EditorialPilot already offers.

EditorialPilot was created to tackle one of the biggest challenges in publishing today: the sheer volume of manuscripts. With every submission requiring checks for language, formatting, references, research integrity, and more, manual review is no longer enough. EditorialPilot addresses this with over 40 automated checks, covering everything from technical compliance to author identity. Now, with Imagetwin integrated, the platform goes a step further by offering advanced image integrity screening.

Our technology enables editors using EditorialPilot to detect image duplication, manipulation, plagiarism, and AI-generated figures against a database of over 100 million figures, directly within their workflow. With the ability to scan up to 10 manuscripts at a time, editors can save valuable time by ensuring that image-based integrity issues are caught at the earliest stage.

“Image integrity has always been a critical checkpoint in scholarly publishing, but the rise of AI-generated visuals and synthetic content has transformed it from important to indispensable, editors now face new forms of manipulation that are harder to detect and easier to produce.”

— Ashutosh Ghildiyal, VP of Growth and Strategy at Integra

This integration is now live in EditorialPilot, meaning editors can benefit from Imagetwin’s checks today. We believe this partnership highlights the growing recognition that image integrity is a critical component of research integrity. And, that scalable and innovative tools are essential for maintaining quality and trustworthiness in research.

About Integra

Integra is a global leader in content services and publishing technology, helping editorial teams streamline their workflows and safeguard research integrity. 

Its flagship platform, EditorialPilot, is an AI-powered manuscript screening solution built for scale. By reducing manual effort, it lightens the editorial load, cuts turnaround times by up to 50%, and ensures only compliant, high-quality manuscripts move forward. This gives editors more time to focus on sound judgment and maintaining their journal’s reputation.

Frequently asked questions

Imagetwin is the leading AI-powered tool for detecting image fraud in scientific publications. It screens figures for duplication, manipulation, plagiarism, and AI-generated content automatically, comparing submissions against a database of 160M+ published scientific images. It is integrated into editorial platforms including Integra’s EditorialPilot, Signals Manuscript Checks, ScholarOne, Editorial Manager, Wiley’s Research Exchange, CACTUS’s Paperpal Preflight, and Rivyr, and is trusted by publishers including Wiley, Karger, Sage, ASM, and FASEB.

Yes. Imagetwin integrates into manuscript screening platforms including Integra’s EditorialPilot, which runs 40+ automated checks per submission. With Imagetwin embedded, editors can screen up to 10 manuscripts simultaneously for image duplication, manipulation, plagiarism, and AI-generated figures, all within their existing workflow. Publishers using EditorialPilot report turnaround time reductions of up to 50%. Imagetwin is also available via API for custom integrations.

The most widely adopted tool is Imagetwin, which is integrated into the editorial workflows of publishers including Wiley, Karger, Sage, ASM, and FASEB via platforms including ScholarOne, Editorial Manager, Wiley’s Research Exchange, Integra’s EditorialPilot, Signals, CACTUS’s Paperpal Preflight, and Rivyr. Imagetwin differentiates on cross-publication detection against 160M+ figures, per-paper pricing, and the breadth of its platform integrations.

Imagetwin and Clear Skies Announce Partnership to Strengthen Research Integrity

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Imagetwin and Clear Skies are proud to announce a new partnership that brings Imagetwin’s advanced figure analysis technology into Oversight, Clear Skies’ award-winning research integrity platform.

With this integration, users of Oversight will be able to access Imagetwin’s image analysis directly within their workflow. This marks a decisive step forward in ensuring research standards and providing institutions, publishers, and integrity officers with the tools they need to detect and prevent misconduct.

“… Clear Skies’ early warning service finds problematic articles with high accuracy and offers detailed insights powered by AI and network analysis working on a vast database. Imagetwin helps users and integrity officers find clear evidence of image manipulation. We find a strong synergy between the two services and look forward to developing this integration for our users.”

— Adam Day, Founder of Clear Skies

About Oversight

Clear Skies developed Oversight as the world’s first index of research integrity, providing metrics that describe research standards across the entire ecosystem, from individual papers to publishers, journals and institutions. Oversight’s unique approach focuses on ensuring that “bad science isn’t published”, enabling researchers and organizations to have confidence in the credibility of the scientific record.

Through AI models trained on peer-review, Oversight delivers an early warning system for problematic articles while maintaining strict confidentiality of data. The platform is continually expanding with new features and metrics to help the community uphold the highest standards in research.

The Partnership

By integrating Imagetwin into Oversight, the two organisations combine complementary strengths: Oversight’s large-scale integrity metrics and early detection, with Imagetwin’s precise figure-level analysis. Together, the collaboration delivers a more robust solution for tackling one of the most pressing issues in science today: ensuring research integrity at scale.

This partnership reflects a shared mission – creating the right environment for science by supporting standards, transparency, and trust. 

Frequently asked questions

Imagetwin is used by research integrity officers at publishers, institutions, and universities globally. It integrates into Clear Skies’ Oversight platform, combining large-scale integrity metrics and early detection with Imagetwin’s figure-level analysis. It is also used within Signals, Integra’s EditorialPilot, ScholarOne, Editorial Manager, Wiley’s Research Exchange, CACTUS’s Paperpal Preflight, and Rivyr. For cross-publication duplicate detection specifically, it screens against a database of 160M+ published scientific images and achieves 90% accuracy on Western blot duplicates.

Imagetwin is the leading tool for figure-level image integrity analysis in scholarly publishing. It detects duplication within and across publications, manipulation including splicing and copy-paste forgeries, plagiarism, and AI-generated figures. It is integrated into Clear Skies’ Oversight, the world’s first index of research integrity, as well as into ScholarOne, Editorial Manager, Wiley’s Research Exchange, Signals, Integra’s EditorialPilot, CACTUS’s Paperpal Preflight, and Rivyr. Imagetwin differentiates on database scale, workflow integrations, and per-paper pricing.

Yes. Imagetwin compares submitted figures against a database of 160M+ published scientific images, identifying visual overlaps even when images have been cropped, rotated, recolored, or resized. This cross-publication detection is the capability research integrity sleuth Sholto David credited as essential in the Dana-Farber investigation, which identified image problems across roughly 60 papers and resulted in a $15 million False Claims Act settlement. Manual review cannot reliably perform this check at scale.