Summary of Existing Work on Secure Medical Image Transfer

A 9.5 KB Excel file summarizing research on a unified system for secure medical image transfer. The dataset, authored by Bicky Yadav and last updated on 2026-05-08, describes a DICOM-compliant framework integrating compression, encryption, and blockchain-based provenance verification. Experimental results focus on clinical MRI and susceptibility-weighted imaging datasets, reporting specific performance metrics.

Use Cases

• Benchmarking image compression techniques based on reported PSNR and SSIM metrics for MRI
• Evaluating cryptographic security for medical images based on described NPCR and UACI scores
• Designing integrated security pipelines for DICOM images based on the described hyperchaotic encryption and key management approach
• Studying blockchain applications for medical data provenance based on the described permissioned blockchain metadata recording

Strengths

• Specific performance metrics are reported, including PSNR (46–51 dB) and SSIM (0.92–0.97) for reconstruction quality
• Compression ratios are quantified, ranging from 7.14:1 to 23.03:1 depending on modality
• Cryptographic properties are detailed with specific values: NPCR 99.6%, UACI 33.46%, entropy 7.9993

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• The dataset is very small (9.5 KB), indicating it is a summary or metadata table rather than a primary image dataset

Provenance

Source

figshare

Collection Method

Likely contains summarized results from the described research paper.

Freshness

Last updated 2026-05-08 17:40:52; freshness should be verified