Image Storage System with Interpretation Context Tracking
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Solution Overview
Problem
Existing data storage systems face inefficiencies when managing large images, leading to increased computing resource consumption and reduced performance in subsequent interpretations, as they lack context on how previous images were interpreted, requiring exhaustive reviews by subsequent interpreters.
Innovation Solution
Implementing a system that segments images and stores them in tiered storage, along with interpretation data packages and moving visual media, which tracks and annotates an interpreter's interest and view paths, allowing for efficient retrieval and reduced data access during subsequent interpretations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If images are stored without interpretation context, then storage simplicity is maintained, but subsequent interpretation efficiency deteriorates due to exhaustive review requirements
Solution Approach 1:
The system performs preliminary actions by capturing and storing interpretation context data (interpreter actions, annotations, view paths) at the time of initial image interpretation. This preliminary capture of contextual information enables subsequent interpreters to quickly understand previous analysis without re-examining entire images, thus improving interpretation efficiency while maintaining manageable storage complexity through selective data capture.
Solution Approach 2:
The storage system is segmented into multiple components: raw image data storage, interpretation context data storage, and metadata storage. This segmentation allows the system to manage complexity by organizing different types of data separately, enabling efficient retrieval of only relevant portions (images or context data) based on interpretation needs, thereby improving productivity without overwhelming storage system complexity.
2Reliability
If complete images are accessed for every interpretation, then interpretation accuracy is maintained, but computing resource consumption increases
Solution Approach 1:
The system extracts and stores only the critical interpretation context elements (key regions of interest, annotations, interpreter actions) from complete image interpretations. This extraction allows subsequent interpretations to rely on extracted context rather than loading and analyzing complete images, maintaining interpretation accuracy through preserved critical information while significantly reducing computing resource consumption by avoiding redundant processing of entire images.
3Productivity
If all image data is loaded for subsequent interpretation, then comprehensive analysis is enabled, but data access time increases
Solution Approach 1:
The system performs preliminary capture and organization of interpretation context data including interpreter actions, annotations, and view paths during initial image analysis. This preliminary action creates a contextual framework that can be quickly accessed during subsequent interpretations, improving data access speed while preventing loss of interpretation context through structured preservation of analytical insights.
Solution Approach 2:
The system introduces interpretation context data as an intermediary between raw image data and subsequent interpretation processes. This intermediary layer provides summarized contextual information (key regions, annotations, view paths) that mediates between complete image data and selective data access, enabling fast access to critical interpretation information without losing contextual nuance, thus improving access speed while preserving interpretation context.
Data Source
AI summary
Methods and systems for managing storage of data are provided. To manage storage of data, images may be stored along with data usable to facilitate subsequent interpretation of the images. The data may provide information to a subsequent interpreter regarding how a previous outcome was made using the image. The data may allow the subsequent interpreter to understand how the previous interpreter viewed portions of the image, the order in which the portion of the images were viewed by the previous interpreter, etc. The subsequent interpreter may be provided with context regarding landmarks or other features of the image added by the previous interpreter and identified by the previous interpreter as being relevant to the outcome.