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ArticleMedical & biological engineering & computing2026

DPCM-DP-EN: a lossless dynamic compress and encrypted encode method for DNA storage of medical images with high storage density.

Kun Bi, Zilin Ma, Qi Xu, Ying Zhou, Yitong Ma, Qingjiang Sun, Zuhong Lu

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Article in Medical & biological engineering & computing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Kun BiState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China. bik@seu.edu.cn.
Zilin MaState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Qi XuState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Ying ZhouState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Yitong MaSoutheast University-Monash University Joint Graduate School, 215123, Suzhou, China.
Qingjiang SunState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Zuhong LuState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.

Funding

National Natural Science Foundation of China 62201141
6 · The paper itself

Abstract

The need for long-term storage of medical images poses a challenge for healthcare organizations, and DNA is anticipated to offer a solution for it. This study proposes an effective DNA storage method (DPCM-DP-EN) for storing medical images, which comprises two key components: (i) In the compress stage, the redundancy between pixels is removed using the differential pulse code modulation (DPCM) method, followed by the use of the ZigZag and the dynamic programming (DP) for further compress; (ii) In the encode stage, a new encrypted (EN)) encode mapping method is proposed to satisfy the biological constraints while ensuring a short time and high density of encode. Tested on three distinct medical image datasets, the results indicate that the DPCM-DP-EN method achieves a compress rate of 40% and above, exceeding other methods by at least 30%. All sequences encoded by DPCM-DP-EN adhere to the GC content and homopolymer constraints, with an encode density of more than 3 bits/nt, significantly surpassing that of other encode methods, and without an impact on the processing time. Additionally, DPCM-DP-EN employs pixel coding, enabling to decode with information lossy at high error rates. In conclusion, the DPCM-DP-EN method provides a viable solution for large-scale storage of medical images (200).

Indexed as

Computer SecurityData CompressionDiagnostic ImagingDNAImage Processing, Computer-AssistedAlgorithmsHumansDNADNA storageEncrypted encodeImage compressMedical imageStorage density

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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.