Scattered Log Semantic Linking for Medical Imaging Analysis
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Solution Overview
Problem
Current medical imaging log file analysis is time-consuming and difficult due to scattered and complex information, requiring skilled engineers and failing to interpret semantic relationships, resulting in inefficient troubleshooting and high costs.
Innovation Solution
A method and device for searching and displaying scattered logs by finding corresponding log data based on keywords, determining timestamps, filtering by time, establishing a coordinate system, semantically linking and dyeing data, and counting related lines to present logs in a simple interface, facilitating semantic analysis and troubleshooting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If log files are analyzed based on syntax and format using existing technology, then search operations can be performed, but the analysis results are discrete data without semantic relationships and require skilled engineers, increasing operation difficulty and cost
Solution Approach 1:
The patent introduces a semantic relationship model as an intermediary layer between log files and analysis results. This model pre-defines semantic relationships among log items from multiple subsystems, allowing the system to automatically interpret and connect scattered log data without requiring skilled engineers to manually analyze complex relationships.
Solution Approach 2:
The patent creates a universal semantic relationship model that can handle log files from multiple different subsystems (imaging chain, post-processing chain, external systems) with a single analysis framework. This multi-functional approach eliminates the need for separate analysis methods for each subsystem, reducing operation difficulty and standardizing the analysis process.
2Loss of information
If log files from multiple subsystems are collected for comprehensive analysis, then more complete information can be obtained, but the log files are scattered and relationships are complicated, increasing time consumption and analysis difficulty
Solution Approach 1:
The patent performs preliminary action by pre-establishing semantic relationship models that define how log items from different subsystems are related. This preparation work is done in advance, so when actual log analysis is needed, the system can quickly retrieve and connect relevant log data using the pre-defined relationships, avoiding time-consuming manual analysis of complex inter-subsystem relationships.
Solution Approach 2:
The semantic relationship model acts as an intermediary that automatically connects scattered log files from multiple subsystems based on pre-defined semantic relationships. This intermediary layer handles the complexity of integrating logs from imaging chain, post-processing chain, and external systems, allowing comprehensive information collection without proportionally increasing analysis time.
3Measurement precision
If semantic relationship model is introduced to interpret log semantics, then better understanding of log relationships can be achieved, but the model construction and maintenance require expertise, potentially increasing system complexity
Solution Approach 1:
The patent implements self-service by enabling the semantic relationship model to automatically adapt and update based on log data patterns. The system can autonomously learn semantic relationships from actual log files and adjust the model accordingly, reducing the need for continuous expert intervention in model construction and maintenance while maintaining high precision in semantic interpretation.
4Loss of information
If detailed log data is presented without organization, then complete information is provided, but the results are hard to read and increase difficulty in troubleshooting
Solution Approach 1:
The patent applies segmentation by dividing the presentation of log data into organized groups based on semantic relationships. Instead of displaying all log data in a single undifferentiated list, the system segments logs by their semantic connections, subsystem origins, and relevance to the search keyword, making the data easier to read and interpret while maintaining completeness.
Solution Approach 2:
The patent adds another dimension to log data presentation by organizing logs not just chronologically but also semantically. This multi-dimensional organization allows users to view log data in different groupings based on semantic relationships, making it easier to understand connections between logs from different subsystems without losing any information.
Data Source
AI summary
A method for searching and displaying scattered logs, comprising: finding out one or more corresponding log data based on a search key word; determining a desired timestamp from the log data, and regarding the log data containing the timestamp as target data; searching a semantic file for related semantic data based on the search key word, and finding out related log data based on the related semantic data; time filtering the related log data to obtain filtered log data; establishing a coordinate system by mapping the target data and the filtered log data onto mapping points of the coordinate system; semantically linking the filtered log data, and dying the filtered log data and the target data; and counting the number of lines related to the target data and the filtered log data, and generating links thereto. The present invention further discloses a device for searching and displaying scattered logs.