Tissue Image Database System for Genomic Data Search
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Solution Overview
Problem
Current digital atlases have limited capabilities for storing, analyzing, and searching two and/or three-dimensional genomic data, particularly in evaluating and manipulating histological image databases, which hinders collaborative research in fields like genomics and neuroscience.
Innovation Solution
A user-accessible tissue sample image system is developed, comprising a database computer unit that stores and processes images of target molecules and anatomical structures, allowing users to upload query images for similarity comparison with stored images, using processing modules and computer program products to facilitate research and information exchange.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing digital atlases are used to store and analyze genomic data, then basic storage capability is provided, but functional and graphical capabilities are limited
Solution Approach 1:
The system integrates multiple functions including image storage, similarity search, 2D/3D visualization, data analysis, and collaborative tools into a single platform. The database computer unit can store various types of data (images, genomic information, anatomical structures) and perform diverse operations through unified interfaces, making the system adaptable to different research needs without requiring separate specialized tools for each function.
Solution Approach 2:
The system embeds multiple levels of data and functionality within each other. Image databases are nested with anatomical structure information, which is further nested with genomic data and functional annotations. The interface layers nest within each other, providing detailed views at multiple levels of abstraction from raw images to processed data to visualizations.
2Productivity
If powerful image evaluation and manipulation capabilities are implemented, then research effectiveness is improved, but system complexity increases
Solution Approach 1:
The system automatically performs image evaluation, similarity matching, and data processing without requiring manual intervention for each operation. The database computer unit autonomously compares query images with stored images, identifies similarities, and returns results based on predefined criteria, reducing the need for complex manual analysis while maintaining high research effectiveness.
Solution Approach 2:
The system introduces intermediate processing layers that automatically transform raw images into processed data representations. Image processing modules serve as intermediaries between the raw image data and the final analysis, automatically extracting features, normalizing data, and preparing information for search and visualization, thereby simplifying the user interface while maintaining powerful capabilities.
3Adaptability or versatility
If collaborative research capabilities are enhanced, then information exchange is improved, but system complexity increases
Solution Approach 1:
The system provides universal access interfaces that allow multiple users to interact with the same database and tools simultaneously. The networked architecture enables different users to perform various operations (searching, analyzing, visualizing) on the same data from different locations, facilitating collaboration without requiring separate systems for each user or institution.
Data Source
AI summary
Disclosed herein is a user-accessible tissue image database system. The system is searchable using a query image provided by a user. The query image is matched with images in the database based on common visual features. Specifically exemplified is the matching of images based on the presence of a target molecule and/or internal anatomical structure.