Extra-Dimensional Demons Algorithm for Image Registration
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Solution Overview
Problem
Conventional image registration methods fail to accurately account for tissue excision or introduction during surgical procedures, leading to spurious distortions and inaccurate registrations in image-guided interventions, particularly in image-guided radiation therapy and surgery.
Innovation Solution
The extra-dimensional Demons (XDD) algorithm adds a fourth dimension to the registration process to explicitly model tissue excision, allowing voxels to be ejected from the image, thereby improving registration accuracy and reducing distortions by identifying and accounting for missing tissue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional deformable registration algorithms are used, then registration speed is maintained, but spurious distortions occur in regions of tissue excision
Solution Approach 1:
The patent adds an extra dimension to the deformation field, transforming it from N-dimensional to N+M-dimensional space. This allows the algorithm to explicitly model tissue excision by ejecting voxels along the extra dimension, preventing spurious distortions that would otherwise occur in conventional N-dimensional registration methods when tissue is physically removed during surgery.
2Ease of manufacture
If rigid registration is used, then computational simplicity is maintained, but geometric accuracy deteriorates due to anatomical deformations
Solution Approach 1:
The patent transitions from rigid (static) registration to deformable (dynamic) registration by introducing a deformation field that can adapt to anatomical changes during intervention. The deformation field is updated iteratively to account for tissue deformations, piecewise-rigid motion, and excisions, maintaining geometric accuracy while preserving reasonable computational efficiency through the extra-dimensional formulation.
3Productivity
If conventional registration methods are used, then processing speed is maintained, but registration accuracy deteriorates in the presence of missing tissue
Solution Approach 1:
By extending the deformation field to N+M dimensions, the algorithm can explicitly represent and handle missing tissue through voxel ejection along the extra dimension. This approach maintains processing efficiency while significantly improving registration accuracy in regions where tissue has been physically removed, compared to conventional methods that interpret missing tissue as deformation.
Data Source
AI summary
A system for registering images includes an image registration unit. The image registration unit is configured to receive first image data for a first image in an N-dimensional space, receive second image data for a second image in the N-dimensional space, calculate a field of update vectors that maps the first image into a moving image, and map the first image into the moving image using the field of update vectors such that the moving image more closely matches the second image. The field of update vectors includes a plurality of N+M dimensional update vectors, each update vector having N spatial components and M extra components. N is a number greater than zero, and M is a number greater than zero. The M extra components of the plurality of update vectors identify portions of the first image that are assigned external values during the mapping the first image into the moving image.