To check whether a microscope image is authentic, start with the original acquisition data—not a screenshot or flattened publication figure. Preserve the source files, compare them with the image in question, and corroborate what you see against metadata, methods, instrument and sample records, and repository copies. A discrepancy calls for investigation; it does not, on its own, prove manipulation, intent, or misconduct.
Start with the original acquisition data
The U.S. Office of Research Integrity (ORI) states that “Authentication of a scientific image requires access to the original data.” A published panel may have been cropped, compressed, combined from channels, or exported without acquisition context. It is therefore a weaker starting point than the microscope’s native acquisition file or a lossless representation that retains relevant image data and metadata.
Ask for both the original acquisition data and the exact file used in the publication or under review. The word “original” depends on the microscopy method and the scale of the data: some workflows produce very large files, so a documented crop, binned image, or compressed derivative may be the practical shareable record. The key is to know what was retained, what was transformed, and how the shared version relates to the acquisition.
Preserve files before inspecting them
- Make an untouched copy of each file you receive, including sidecar metadata and related acquisition records. Keep the received version separate from working copies.
- Record the file’s source, receipt date, filename, and any conversion or export steps you perform.
- Inspect and annotate a duplicate, not the preserved original. ORI’s guidance recommends retaining originals and making image manipulations on copies.
- Where possible, retain the native microscope format. If conversion is necessary, use a lossless representation when feasible and document the conversion. ORI’s older guidance recommends TIFF for conversion and cautions against JPEG for most scientific images because its compression is lossy; no single format is sufficient for every microscopy workflow.
OME-TIFF is one open format that can retain metadata and support reanalysis. Whether it preserves the information needed for a particular image depends on the data and conversion, so verify what is included rather than relying on the extension alone.
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Check metadata against the experiment
Inspect embedded metadata and sidecar files for details that are available, such as acquisition date, instrument and detector, objective or pixel scale, channels, exposure or other acquisition settings, and processing history. Then compare those details with the paper’s methods, instrument logs, sample labels, and repository records.
Metadata is useful corroboration, not a verdict. Microscope vendors store information differently, and fields may be incomplete. Exporting a file or uploading it to a sharing platform can remove metadata. Missing EXIF-like fields do not establish tampering; microscopy formats may store information in other structures.
A 2021 QUAREP-LiMi initiative paper described the need for human-readable methods, machine-readable provenance metadata, and instrument quality-control metrics. It also reported that no universally accepted provenance and QC metadata guidelines existed across different imaging types at that time. In practice, assess whether the available records make the particular image and its processing understandable, rather than expecting every microscope to produce one standardized metadata record.
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Compare the questioned image with its source
Place the publication panel and acquisition data at matching scale and compare the image content, channels, crop, background, and panel boundaries. If the file contains multiple channels, check them separately as well as in the displayed composite. Note repeated regions, abrupt discontinuities, local changes that lack an explanation, inconsistent scale bars, or annotations that obscure relevant information.
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These are signals to examine, not automatic proof of alteration. Resampling, compression, contrast adjustments, stitching, and other legitimate processing can change how an image looks or introduce visual artifacts. Ask what processing was applied, whether it was disclosed, and whether it was applied consistently to the relevant images or comparison group. For quantitative conclusions, request the analysis workflow and the source data behind reported measurements.
A 2023 community-developed checklist recommends that processing not overwrite the original and that both the original image and the published version be accessible. It also emphasizes clear, representative, reproducible data and enough methods and analysis information to support understanding and reanalysis.
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Corroborate the image with independent records
Check whether the image’s account is consistent with the paper’s methods, specimen details, instrument settings, other panels or replicates, repository deposits, and documented file-handling history. These sources can help establish whether the image fits the described experiment, but a record that looks plausible does not by itself prove that the depicted specimen is the one claimed.
For apparent irregularities, ask a microscopy specialist whether the instrument, specimen, acquisition, or processing could explain them. If the matter is consequential, original files are missing, or several related anomalies appear, a qualified image-forensics examiner may be appropriate. The Scientific Working Group on Imaging Technology’s FBI-archived Best Practices for Image Authentication describes the task as applying image science and domain expertise to assess whether a questioned image accurately represents original data by defined criteria.
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Keep the conclusions distinct: a visual discrepancy is an observation; its scientific explanation requires context; and a misconduct determination belongs to the relevant institutional process. ORI’s forensic examples ask how one can show that three lanes are the same data, and which data were fabricated and how. The latter is an exercise prompt, not an allegation about any particular image.
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Understand what each check can establish
| Check | What it can support | What it cannot establish by itself |
|---|---|---|
| Original acquisition file | A basis for comparing the publication image with source data. | That the sample label or experimental claim is correct without context. |
| Metadata and instrument records | Acquisition and processing details, where the records are present and reliable. | That an image is true merely because its fields look plausible. |
| Hash comparison | That two files are byte-for-byte copies of the same hashed file. | That the image faithfully depicts the specimen or that it was not altered before hashing. |
| Visual forensics | Possible duplicated, altered, or inconsistent regions warranting review. | Intent, misconduct, or a definitive verdict from an initial check. |
| C2PA credentials or a watermark result | A provenance signal within the system’s adoption and verification scope. | A complete history if steps are unsupported or metadata was stripped. |
| Independent methods, sample, and repository records | Corroboration across evidence sources. | Certainty when original data or reliable records are unavailable. |
A cryptographic hash is especially easy to overinterpret. If the hash of a working copy matches the hash recorded earlier, that supports the conclusion that the copy has not changed since that point. It does not authenticate the original capture or show that the pixels represent the claimed specimen.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Use provenance credentials as supporting evidence
ORI describes C2PA Content Credentials as signed provenance information that can record who or what created or edited a supported file and what modifications were made. It also describes SynthID as an image watermark checked through Google’s verification systems. These are different mechanisms, and neither necessarily covers every tool or handoff in a scientific imaging workflow.
A missing credential or watermark does not prove that an image is false or authentic: the software may not have created one, a platform may have stripped metadata, or the provenance chain may not cover every step. A valid credential can document file history within its coverage, but it does not decide whether a scientific adjustment was justified. Treat these results as one supporting strand alongside original data and expert interpretation. See ORI’s Content Provenance guidance for its descriptions of these systems and their limits.
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When the evidence remains inconclusive
Sometimes the original acquisition files or reliable records are unavailable. In that case, state what could and could not be checked: for example, whether a published panel can be compared with a source file, whether metadata survives, and whether independent records corroborate the described experiment. Do not turn the absence of records into proof of deception, or treat a plausible-looking figure as authenticated.
For research-data retention and access, follow the institution’s secure storage and retention practices. Keeping a separate backup helps preserve files, but storage hardware does not detect manipulation or authenticate an image.
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