Medical Image Standardization for Tracer Uptake Analysis
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Solution Overview
Problem
Current medical imaging technologies face challenges in accurately and efficiently analyzing and displaying medical images due to inconsistencies in ROI markings, image distortion, and the need for human intervention, leading to low analysis efficiency and inaccurate results.
Innovation Solution
Systems and methods that transform medical images into a standard space, segment body portions, and adjust image parameters to improve clarity and readability, while integrating disease risk information for automated image display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual ROI marking and image analysis methods are used, then doctors can perform image analysis, but the analysis efficiency is low and results are inaccurate due to inconsistencies in markings
Solution Approach 1:
The system enables automated image analysis by having the computer system perform ROI identification, segmentation, and parameter measurement automatically without requiring manual marking by doctors. The algorithm processes images independently, extracting features and generating analysis results self-service style, which eliminates human inconsistency and improves both efficiency and accuracy.
Solution Approach 2:
The patent replaces the manual mechanical process of doctor marking and visual analysis with an automated computer-based image processing system. The system uses algorithms to detect, segment, and measure image features automatically, substituting human manual operations with computational processes that are more consistent and efficient.
2Illumination intensity
If traditional image display methods are used, then images can be displayed, but image distortion occurs and clarity is reduced
Solution Approach 1:
The system automatically adjusts image display parameters such as brightness, contrast, and color mapping based on the extracted features and tracer uptake information. By dynamically changing these display parameters, the system enhances image clarity and readability while compensating for any distortion, ensuring optimal visualization of medical data.
3Productivity
If automated image processing is implemented, then analysis efficiency improves, but device complexity increases
Solution Approach 1:
The patent integrates multiple functions including ROI identification, image segmentation, feature extraction, parameter measurement, and image display enhancement into a single unified system. This multi-functional approach consolidates what would otherwise require multiple separate devices or manual processes, achieving high automation efficiency while managing system complexity through integration.
Data Source
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AI summary
Systems and methods for image processing are provided. The systems obtain a plurality of images of a target subject that are captured consecutively over time. The target subject is injected with tracer and including a target body portion. For each of the plurality of images, the systems generate a sub-image of the target body portion by segmenting the image and transform the sub-image to generate a transformed sub-image in a standard space based on a template image of the target body portion. The standard space includes a plurality of template images of a plurality of body portions. The systems further determine an uptake variation curve indicating a change of tracer uptake in the target body portion over the time based on the transformed sub-images corresponding to the plurality of images.