X-Ray Motion Emphasis Imaging for Clearer Moving Target Visibility
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Solution Overview
Problem
Existing X-ray diagnostic systems face challenges in effectively emphasizing the target components while suppressing non-target components, leading to reduced visibility due to the emphasis of non-target elements like bones and diaphragms during image processing.
Innovation Solution
The system generates an emphasis processing image by compositing the X-ray image with an extracted motion-related component, using motion suppression images and emphasis processing techniques to enhance the target while minimizing the impact of non-target components, employing methods such as mean or median value images, difference images, and multi-frequency processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple kinds of processing are performed on medical images to extract useful information, then diagnostic accuracy is improved, but processing time increases and prevents timely diagnosis
Solution Approach 1:
The system performs preprocessing operations (noise filtering, contrast enhancement, edge detection) on medical images before full diagnostic processing. This preliminary action prepares the images in advance, reducing the computational burden during critical diagnostic processing and enabling faster turnaround without sacrificing diagnostic accuracy.
Solution Approach 2:
The image processing workflow is divided into multiple segments: preprocessing, diagnostic processing, and postprocessing. Each segment handles specific tasks independently, allowing parallel processing and optimization of each stage. This segmentation enables the system to manage complex processing requirements while maintaining efficient throughput and timely diagnosis.
2Measurement precision
If noise filtering is performed on medical images, then image quality is improved, but processing time increases
Solution Approach 1:
The noise filtering process applies adaptive filtering that processes only the portions of the image requiring enhancement rather than uniformly processing the entire image. This partial action approach maintains image quality in critical regions while reducing overall processing time by avoiding redundant operations in already-clear areas.
3Measurement precision
If edge enhancement processing is performed on medical images, then lesion detectability is improved, but processing time increases
Solution Approach 1:
The edge enhancement processing applies different processing intensities to different regions of the image based on local characteristics. Areas containing potential lesions receive enhanced processing to improve detectability, while uniform regions receive minimal processing. This local quality approach optimizes lesion detectability while minimizing overall processing time.
Data Source
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AI summary
According to one embodiment, a medical image processing apparatus includes an acquisition unit, an extraction unit, and an emphasis processing image generation unit. The acquisition unit is configured to acquire a plurality of time-series X-ray images of an object. The extraction unit is configured to extract a motion related component in each of the plurality of X-ray images. The emphasis processing image generation unit is configured to generate an emphasis processing image in which a moving target is emphasized in each of the plurality of X-ray images based on the extracted motion related component.