Intervertebral Disc Image Reconstruction Using Spine Centerline Orientation
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Solution Overview
Problem
Computed tomography (CT) images of intervertebral discs often fail to meet clinical diagnostic requirements due to variations in patient anatomy, such as spinal curvature and disc size, making it challenging to accurately image and diagnose intervertebral disc issues.
Innovation Solution
An image processing method that involves acquiring CT images, generating CT value images, identifying the optimal sagittal image, determining the centerline of the spine, and reconstructing images of intervertebral discs based on their center point and direction, using techniques like minimum density projection and morphological dilation to enhance image accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional CT imaging is used for intervertebral discs, then the imaging process is simple and quick, but the diagnostic accuracy is insufficient due to patient anatomical variations
Solution Approach 1:
The imaging system segments the spine into individual vertebral bodies and intervertebral discs, identifying each disc's unique center point and orientation. This segmentation allows customized imaging parameters for each disc, improving diagnostic accuracy while managing complexity through automated processing.
Solution Approach 2:
The system applies local quality by determining specific imaging parameters (center point, direction, orientation) for each intervertebral disc based on its anatomical location. This allows the imaging system to adapt to local anatomical variations rather than using uniform imaging parameters throughout the spine.
2Measurement precision
If CT images are acquired without processing for anatomical variations, then the imaging process is fast, but the images do not satisfy clinical diagnostic requirements
Solution Approach 1:
The system performs preliminary actions by automatically identifying vertebral bodies, determining disc center points and orientations, and establishing optimal imaging parameters before actual disc imaging. This preliminary processing enables accurate diagnostic images while reducing overall processing time through automated workflows.
Solution Approach 2:
The imaging system performs self-service by automatically analyzing anatomical structures, determining disc parameters, and configuring imaging settings without requiring manual intervention. This automation improves image accuracy while minimizing the time loss associated with manual processing.
3Adaptability or versatility
If standard CT imaging protocols are used, then the imaging procedure is straightforward, but it cannot account for variations in spinal curvature and disc orientation
Solution Approach 1:
The imaging system implements dynamics by adapting imaging parameters dynamically based on each disc's anatomical characteristics. The system determines the center point, direction, and orientation for each disc individually, allowing the imaging protocol to flex and adapt to variations in spinal curvature and disc alignment rather than following a rigid standard protocol.
Data Source
AI summary
The present disclosure directs to a system and method for image processing. The method for image processing comprises acquiring a plurality of original computed tomography (CT) images of a spine of a subject; generating CT value images of the spine of the subject by processing the plurality of original CT images. The method further includes identifying an optimal sagittal image in which a centerline of the spine is located based on the CT value images. The method further includes identifying the centerline of the spine within the optimal sagittal image. The method further includes identifying a center point and a direction of at least one intervertebral disc along the centerline of the spine. The method still further includes reconstructing an image of the at least one intervertebral disc based on the center point and the direction of the at least one intervertebral disc.