ArticleJournal of pathology informatics2026
Comparison and image analysis of different file formats on whole-slide images for colorectal and non-small cell lung carcinomas.
Article in Journal of pathology informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Different scanners employ various image acquisition techniques and may store scanned images in proprietary formats or export them to a range of standard file formats. Understanding these technical limitations is essential for ensuring optimal scan quality and accurate image analysis. The present study compared image formats from two whole-slide imaging platforms-Leica's Aperio AT2 (.SVS) and 3DHistech's Panoramic P250 Flash III (.MRXS)-using artificial intelligence (AI) algorithms to quantify pixel-level, color-profile, and segmentation differences on 10 colorectal carcinoma (CRC) and 10 non-small cell lung carcinoma (NSCLC) cases. The same slides were scanned independently on both platforms at 20×, and native MRXS files were also converted to SVS using SlideMaster®, allowing us to isolate the effect of file-format translation (native MRXS vs. MRXS-to-SVS, same scanner) from that of scanner hardware (3DHistech-derived formats vs. native Aperio SVS). Native MRXS and MRXS-to-SVS files showed very high similarity in pixel values, color profile, and AI predictions, whereas native Aperio SVS files differed significantly across image size, pixel size, pixel number, and color profile-reflecting the combined effect of scanner hardware and file format rather than format alone. Given the limited sample size and absence of a pre-specified power analysis, these findings are exploratory and hypothesis-generating. We anticipate that an enterprise-level communication standard will emerge to harmonize image formats and support consistent, reproducible analysis by pathologists and AI software alike.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.