Medical Image Series Navigation via Extracted Separation Data
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Solution Overview
Problem
Manual navigation between multiple related medical image series is time-consuming and unreliable, and existing automatic navigation systems are memory-intensive and exhibit slow performance due to the need to store entire image series locally.
Innovation Solution
A method and system that navigate image series by receiving a reference location input, determining a target position using initial series data and separation distance, and calculating a target distance to efficiently determine the target position without storing extensive image data locally, thereby reducing memory requirements and improving performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If entire series of medical images are stored on local memory for navigation, then navigation between multiple related image series can be achieved, but memory usage increases and performance becomes slow
Solution Approach 1:
The patent extracts only the essential navigation-related data (initial series data and separation distance) from the complete image series, storing only this extracted information locally while maintaining the ability to navigate between images. This resolves the contradiction by removing unnecessary image data from local storage while preserving navigation functionality.
Solution Approach 2:
The patent segments the image series data into two parts: essential navigation data (stored locally) and full image data (stored remotely or on demand). This segmentation allows the system to maintain navigation reliability with minimal local storage requirements, as only the segmented navigation parameters are kept locally rather than the entire image series.
2Reliability
If entire series of medical images are stored on local memory for navigation, then navigation between multiple related image series can be achieved, but navigation speed decreases
Solution Approach 1:
By extracting and storing only the critical navigation parameters (initial location and separation distance) rather than entire image series, the system achieves fast navigation calculations while maintaining reliability. The extraction principle enables quick computation of target positions without the computational overhead of processing complete image datasets.
3Ease of operation
If manual navigation between different series of images is used, then flexibility in reviewing images is maintained, but navigation time increases
Solution Approach 1:
The system provides automatic navigation feedback by calculating and displaying target image positions based on reference locations and separation distances. This feedback mechanism maintains operational flexibility while eliminating manual navigation time, as the system automatically determines and presents the next relevant image based on the stored navigation parameters.
Data Source
AI summary
A method and system are provided for navigating an image series that includes at least one image. The method and system involve receiving an input corresponding to a reference location; operating at least one processor for determining a target position in the image series based on the reference location, the at least one processor being configured to receive initial series data corresponding to an initial location in the image series and a separation distance corresponding to a distance between two sequential images in the image series; determine a target distance for the image series, the target distance corresponding to a distance from the reference location to the initial location; and determine the target position based on the separation distance and the target distance.