Evidence map›Paper›PMID 42102108›Full record

ArticlePloS one2026

Secure near-lossless medical image compression and encryption with image-specific post-quantum key management and blockchain-based verification.

Bicky Yadav, Megha Arakeri

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Bicky YadavManipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India.
Megha ArakeriManipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India.ORCID https://orcid.org/0000-0003-0340-5794

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Secure image transfer is a critical requirement in telemedicine and Picture Archiving and Communication Systems (PACS), where diagnostic integrity and patient confidentiality must be simultaneously ensured. High-resolution medical images, especially Magnetic Resonance Imaging (MRI), are often transferred over bandwidth-limited networks without impairing diagnostic quality or confidentiality against unauthorized access, manipulation, and replay. Existing approaches generally rely on a cascaded pipeline where image compression, encryption, and verification are considered as separate, independent operations. These distributed designs are prone to cryptographic key management issues, suffer from non-deterministic error control, lack meaningful coupling between image identity and cryptographic state, and provide no verifiable provenance or post-quantum key migration support. In this paper, we propose a DICOM-compliant system that integrates [Formula: see text]-regularized near-lossless image compression, hyperchaotic permutation diffusion encryption, post-quantum secure key establishment, and blockchain-based provenance verification as a unified operation. JPEG 2000 is used for primary image compression, and a residual refinement layer is introduced to limit residual correction amplitudes by [Formula: see text]-regularization to retain diagnostically significant information. Hyperchaotic encryption is performed with a symmetric image key generated using the NIST-standard post-quantum Key Encapsulation Mechanism (ML-KEM) and extracted using the HMAC-based Key Derivation Function (HKDF), cryptographically linked to DICOM image metadata. Message integrity is ensured using a keyed-hash message authentication code (HMAC), while a permissioned blockchain records only non-sensitive cryptographic metadata to enable verifiable provenance. Experimental results on clinical MRI and susceptibility-weighted imaging datasets demonstrate high reconstruction quality (PSNR: 46-51 dB, SSIM: 0.92-0.97), compression ratios ranging from 7.14:1 to 23.03:1 depending on modality and [Formula: see text], and strong cryptographic properties (NPCR: 99.6%, UACI: 33.46%, entropy: 7.9993). The evaluation focuses on MRI-based modalities, reflecting the intended scope of this study.

Indexed as

BlockchainComputer SecurityData CompressionImage Processing, Computer-AssistedAlgorithmsCompression AlgorithmsConfidentialityHumansMagnetic Resonance ImagingRadiology Information Systems

Identifiers

PMID42102108
PMCPMC13155624

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Registered trials

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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.