Volumetric Bone Change Quantification Using CT Image Registration
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Solution Overview
Problem
Current methods for assessing bone loss in dental therapies, such as periodontal and implant therapies, rely on two-dimensional radiographs, which are prone to projection errors and lack three-dimensional information, making it difficult to accurately quantify local bone or soft tissue changes and evaluate the success of treatments like bone augmentation and implant therapy.
Innovation Solution
A method and system for volumetric quantification of local bone changes using semi-automatic segmentation and image registration, where computed tomography images are registered to a common coordinate system, and a region of interest is selected using anatomical landmarks and clipping planes to segment and calculate bone volume changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If two-dimensional radiographs are used for bone assessment, then the imaging process is simple and quick, but projection errors occur and three-dimensional information is lost
Solution Approach 1:
The patent transitions from two-dimensional radiographic imaging to three-dimensional CT imaging to eliminate projection errors and provide accurate volumetric bone assessment. The 3D imaging modality allows differentiation of buccal and lingual cortical plates and provides true spatial information about bone structures that cannot be obtained with conventional 2D radiographs.
2Measurement precision
If three-dimensional CT imaging is used for bone assessment, then accurate volumetric information is obtained, but the complexity of image processing and analysis increases
Solution Approach 1:
The patent applies segmentation to divide the 3D CT image data into distinct anatomical regions including bone, soft tissue, and air spaces. This segmentation process breaks down the complex volumetric data into manageable components that can be individually analyzed and quantified, reducing the overall processing complexity while maintaining measurement accuracy.
Solution Approach 2:
The patent extracts the bone volume information from the complete 3D CT dataset by isolating and segmenting only the relevant bony structures. This extraction process removes unnecessary information and focuses computational resources on the specific anatomical features needed for bone loss assessment, thereby simplifying the analysis workflow.
3Manufacturing precision
If manual segmentation of bone structures is performed, then detailed control over region selection is achieved, but user-dependent errors and time consumption increase
Solution Approach 1:
The patent implements preliminary automated preprocessing steps including image registration, noise filtering, and initial bone tissue classification before manual segmentation. These preparatory actions reduce the workload during the manual delineation phase by pre-identifying potential bone regions and establishing a standardized coordinate system, thereby decreasing both processing time and user-dependent variability.
4Measurement precision
If image registration is performed to align multiple scans, then accurate comparison of bone changes over time is enabled, but computational requirements and processing time increase
Solution Approach 1:
The patent applies partial image registration by aligning only the critical anatomical landmarks and regions relevant to bone assessment rather than performing complete volumetric registration of the entire dataset. This partial approach maintains sufficient accuracy for detecting bone changes while significantly reducing computational energy consumption and processing time compared to full registration methods.
Data Source
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AI summary
A method and system are described for volumetric quantification of local bone changes. The method comprises the steps of loading at least a first and second (cone-beam) computed tomography three dimensional image, registering said at least a first three dimensional image and second three dimensional image to one coordinate system, selecting a region of interest in one of said first three dimensional image or said second three dimensional image, for said first three dimensional image and said second three dimensional image, segmenting the local bone within the region of interest by segmenting voxels related to air and/or soft tissues within the region of interest and attributing these voxels to an outside region, while the volume formed by the remaining volume represent the local bone or the local bone with soft tissue, and calculating of the volume of local bone in the first three dimensional image and the volume of local bone in said second three dimensional image and subtracting said first volume from said second volume and defining the difference as the local bone change or the change in local bone with soft tissue.