Gaze-Based Window Leveling for Medical Image Review
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Solution Overview
Problem
Medical image review efficiency is hindered by the need for manual window leveling adjustments, which require significant user interaction and skill, as radiologists must repeatedly adjust settings to optimize image visibility across varying pixel value ranges within an image.
Innovation Solution
A method that automatically applies window leveling based on the user's gaze location, determining a region of interest and adjusting window level values accordingly, allowing for adaptive and efficient image visualization without user input beyond focusing on specific image portions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual window leveling adjustment is used, then the user can control image visualization, but the review efficiency decreases due to repeated manual adjustments
Solution Approach 1:
The system automatically performs window leveling adjustments based on detected regions of interest without requiring manual user intervention. The computer identifies anatomical structures and autonomously optimizes display parameters, allowing the system to serve itself rather than requiring continuous user operation.
Solution Approach 2:
The system pre-processes the medical image to identify regions of interest and pre-calculates optimal window leveling parameters before the user views the image. This preliminary analysis enables immediate optimized display without requiring the user to perform iterative adjustments during review.
2Manufacturing precision
If manual window leveling adjustment is performed, then the user can optimize image visibility, but the time required for adjustments increases
Solution Approach 1:
The patent replaces the mechanical interaction of manual mouse-based window leveling with an automated computer vision system. The system uses image processing algorithms to automatically detect anatomical features and calculate optimal display parameters, substituting manual mechanical adjustment with automated computational analysis.
Solution Approach 2:
The system introduces an intermediary automated window leveling module that acts as a mediator between the raw medical image and the final displayed image. This intermediary automatically analyzes the image content and applies appropriate display parameters, eliminating the need for direct manual user manipulation.
3Device complexity
If fixed window leveling is applied to the entire image, then the display is simple, but it cannot optimize different anatomical regions with different pixel value ranges
Solution Approach 1:
The system applies different window leveling parameters to different regions of the image based on the specific anatomical structures present in each region. Each region of interest receives customized display optimization tailored to its unique pixel value characteristics, allowing local adaptation rather than uniform global settings.
Solution Approach 2:
The medical image is segmented into multiple regions of interest based on detected anatomical structures. Each segmented region is then independently analyzed and assigned appropriate window leveling parameters, dividing the image into functional zones that can be optimized separately rather than treating the entire image as a single uniform entity.
Data Source
AI summary
A method, a computing device and a computer program product are provided in order to automatically apply window leveling to an image, such as a medical image. In the context of a method, a gaze location within an image is determined based upon a determination that a user is staring at the gaze location. The method also determines a region of interest within the image based upon the gaze location and determines pixel values for pixels within the region of interest. The method also establishes window level values based upon the pixel values for pixels within the region of interest and applies window leveling based upon the window level values established based upon the pixel values for pixels within the region of interest.