Causal Multi-Stream Lossless Compression of Multimodal Volumetric Magnetic Resonance Imaging with Explicit Physical Payload Accounting
Co-registered multimodal magnetic resonance imaging (MRI) contains redundancy within each volume and across an ordered set of contrasts. A lossless codec can exploit this dependence only if a standalone decoder can reproduce every prediction, context query, and payload boundary. We present MM-CLICK, the proper name of the evaluated codec rather than an expandable acronym, as a causal framework for four-volume MRI streams, not as a new predictor or entropy-coding primitive. The codec fixes the FLAIR → T1w → T1gd → T2w serialization, integrates established causal prediction and context-adaptive coding components through decoder-reproducible state updates, regenerates probability contexts from reconstructed samples, and includes boundary data and decoder-required assets in the physical payload. On TEST266 (n = 266), MM-CLICK achieved 1.0877 complete physical bits per source scalar (bpp), compared with 1.0778 bpp for HEVC-RExt; the paired difference was not statistically significant (Wilcoxon p = 0.1873). The measured rate was lower than that of JPEG-LS (1.3626 bpp), reversible JPEG2000 (1.5259 bpp), and BCM-Net (1.3470 bpp) under their stated physical-object scopes. Standalone decoding exactly reconstructed all 266 canonical little-endian uint16 arrays. These results demonstrate a reproducible lossless MRI codec that combines causal multimodal organization, decoder-regenerated contexts, physical payload accounting, and bit-exact verification.
Authors
- Yiwen Xu (ORCID: https://orcid.org/0000-0003-0523-4773)
- Nian He (ORCID: https://orcid.org/0009-0007-6085-7160)
- Zheng Hui
- Wenjie Fang
Institutions
- Fuzhou University Zhicheng College (CN)
- Fuzhou University (CN)
Publication Details
- Journal
- Entropy
- Published
- 2026-11-09
- DOI
- https://doi.org/10.3390/e28111232
- Primary Topic
- Advanced Data Compression Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00