Scholarlink

Some universities have created digital slices from pathological slides and established a digital pathological slide database to enable anytime, anywhere, and any-person collaborative reading, which improves teaching quality. Due to the particularity of pathological digital slides, image quality can affect the diagnosis of pathological results, and there are high requirements for the production and storage of images. If there are security risks such as unclear image data, image replacement, and image loss, they will have an impact on teaching quality. To address these issues, this article proposes a pathological digital slide storage solution based on intelligent contracts and non-fungible tokens. The solution outlines the concept of SVG (Scalable Vector Graphics), NFT (Non-Fungible Token), and IPFS (InterPlanetary File System). The solution designs a method of embedding and storing pathological digital slides and descriptive information using SVG, while storing the images in IPFS. The Solidity smart contract based on the ERC-721 standard is used to realize the creation and querying of NFTs for SVG digital slides. Experimental testing on the Ethereum test chain has shown that SVG digital slides have lower gas consumption than traditional image storage methods, and the performance indicators of the smart contract are within the acceptable range for users. The stored data has characteristics such as high fidelity, scalability, non-tamperability, traceability, uniqueness, and authenticity, ensuring the security of pathological digital slides and comprehensively improving pathological teaching quality.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Pathology Digital Slice Storage Model Based on Smart Contract Non-homogeneous Tokenization

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Yiran Wang,
  • Dongxiang Song,
  • Shoujian Duan,
  • Jun Pan,
  • Yongxian Pu

摘要

Some universities have created digital slices from pathological slides and established a digital pathological slide database to enable anytime, anywhere, and any-person collaborative reading, which improves teaching quality. Due to the particularity of pathological digital slides, image quality can affect the diagnosis of pathological results, and there are high requirements for the production and storage of images. If there are security risks such as unclear image data, image replacement, and image loss, they will have an impact on teaching quality. To address these issues, this article proposes a pathological digital slide storage solution based on intelligent contracts and non-fungible tokens. The solution outlines the concept of SVG (Scalable Vector Graphics), NFT (Non-Fungible Token), and IPFS (InterPlanetary File System). The solution designs a method of embedding and storing pathological digital slides and descriptive information using SVG, while storing the images in IPFS. The Solidity smart contract based on the ERC-721 standard is used to realize the creation and querying of NFTs for SVG digital slides. Experimental testing on the Ethereum test chain has shown that SVG digital slides have lower gas consumption than traditional image storage methods, and the performance indicators of the smart contract are within the acceptable range for users. The stored data has characteristics such as high fidelity, scalability, non-tamperability, traceability, uniqueness, and authenticity, ensuring the security of pathological digital slides and comprehensively improving pathological teaching quality.