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Previewable Contract-Based On-Chain X-Ray Image Sharing Framework for Clinical Research.
Li, Megan Mun; Kuo, Tsung-Ting.
  • Li MM; University of California San Diego, La Jolla, CA, USA.
  • Kuo TT; University of California San Diego, La Jolla, CA, USA. Electronic address: tskuo@health.ucsd.edu.
Int J Med Inform ; 156: 104599, 2021 12.
Article in English | MEDLINE | ID: covidwho-1440101
ABSTRACT

BACKGROUND:

An image sharing framework is important to support downstream data analysis especially for pandemics like Coronavirus Disease 2019 (COVID-19). Current centralized image sharing frameworks become dysfunctional if any part of the framework fails. Existing decentralized image sharing frameworks do not store the images on the blockchain, thus the data themselves are not highly available, immutable, and provable. Meanwhile, storing images on the blockchain provides availability/immutability/provenance to the images, yet produces challenges such as large-image handling, high viewing latency while viewing images, and software inconsistency while storing/loading images.

OBJECTIVE:

This study aims to store chest x-ray images using a blockchain-based framework to handle large images, improve viewing latency, and enhance software consistency. BASIC PROCEDURES We developed a splitting and merging function to handle large images, a feature that allows previewing an image earlier to improve viewing latency, and a smart contract to enhance software consistency. We used 920 publicly available images to evaluate the storing and loading methods through time measurements. MAIN

FINDINGS:

The blockchain network successfully shares large images up to 18 MB and supports smart contracts to provide code immutability, availability, and provenance. Applying the preview feature successfully shared images 93% faster than sharing images without the preview feature. PRINCIPAL

CONCLUSIONS:

The findings of this study can guide future studies to generalize our framework to other forms of data to improve sharing and interoperability.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Diagnostic Imaging / Blockchain Type of study: Experimental Studies / Prognostic study Limits: Humans Language: English Journal: Int J Med Inform Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: J.ijmedinf.2021.104599

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Diagnostic Imaging / Blockchain Type of study: Experimental Studies / Prognostic study Limits: Humans Language: English Journal: Int J Med Inform Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: J.ijmedinf.2021.104599