Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Software . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
ZENODO
Software . 2026
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

Project Omran: Non-Equilibrium Thermodynamic Decomposition of Raw DICOM Fields via Fractional ADMM Solvers

Authors: Osman Mohamed Ahmed, Omran;

Project Omran: Non-Equilibrium Thermodynamic Decomposition of Raw DICOM Fields via Fractional ADMM Solvers

Abstract

Project Omran: Non-Equilibrium Thermodynamic Decomposition Solver. This software implements an advanced ADMM Split-Bregman framework to decompose raw DICOM fields into four irreducible physical components: structural anatomy, instrumentation hardware noise, biological quantum-thermodynamic entropy, and pure white noise residuals. Validated in-silico with GPU acceleration (PyTorch), proving absolute mathematical isolation of sub-resolution cellular metabolic anomalies (SNR ~ 0 dB) for early oncology diagnostics.

Project Omran: Non-Equilibrium Thermodynamic Decomposition Solver. This software implements an advanced ADMM Split-Bregman framework to decompose raw DICOM fields into four irreducible physical components: structural anatomy, instrumentation hardware noise, biological quantum-thermodynamic entropy, and pure white noise residuals. Validated in-silico with GPU acceleration (PyTorch), proving absolute mathematical isolation of sub-resolution cellular metabolic anomalies (SNR ~ 0 dB) for early oncology diagnostics.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average