OCT and Visualization Module Calibration via Cascaded Image Registration
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Solution Overview
Problem
Existing imaging systems face challenges in aligning optical coherence tomography (OCT) images with other modalities, particularly due to the complexity of mechanical scanning and the time-consuming nature of manual and semi-automatic calibration processes.
Innovation Solution
An imaging system with a controller that generates a scanning pattern, synchronously acquires OCT data, and performs cascaded image registration to align OCT and visualization data, utilizing a robotic arm for precise movement and affine diffusion tensor image registration to compensate for mismatches in rotation, shear, and scaling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration is used to align OCT and visualization images, then alignment accuracy can be achieved, but the process becomes time-consuming and requires experienced technical staff
Solution Approach 1:
The system performs preliminary actions by automatically generating a scanning pattern for a calibration region and acquiring OCT data before the actual calibration is needed. The cascaded image registration process is pre-configured with coarse and fine registration stages, so when calibration is required, the system can quickly execute the pre-planned registration steps without requiring manual intervention or waiting for technical staff availability.
Solution Approach 2:
The system performs self-service calibration through automated image registration. The controller automatically generates scanning patterns, acquires OCT data, performs coarse registration to correct large misalignments, and executes fine registration to achieve precise alignment. This self-calibration process eliminates the need for experienced technical staff to manually perform calibration, significantly reducing both time requirements and dependency on specialized personnel.
2Adaptability or versatility
If mechanical scanning is used in point-scanning OCT systems, then imaging capability is maintained, but the complexity of aligning images from OCT with other modalities increases
Solution Approach 1:
The system replaces complex mechanical alignment procedures with computational image registration methods. Instead of relying on mechanical adjustments to align OCT and visualization images, the controller performs coarse registration using translation transformation matrices and fine registration using affine diffusion tensor image registration. This substitution of mechanical alignment with software-based registration simplifies the overall system complexity while maintaining the mechanical scanning capability for imaging.
Solution Approach 2:
The system introduces an intermediary computational process between the mechanical scanning system and the final aligned images. The cascaded image registration process acts as an intermediary that takes raw OCT data and visualization data, processes them through coarse and fine registration stages, and produces aligned output. This intermediary registration process decouples the mechanical scanning complexity from the alignment task, allowing each to be optimized independently.
3Extent of automation
If semi-automatic calibration is used, then some automation is achieved, but the process remains tedious and requires significant human intervention
Solution Approach 1:
The system achieves full automation through self-service calibration. The controller automatically generates scanning patterns, acquires OCT data synchronously with visualization data, performs coarse registration to correct large misalignments, and executes fine registration to achieve precise alignment. The entire calibration process occurs without human intervention, making the system easy to operate while maintaining high automation. Users simply need to initiate the calibration process, and the system handles all subsequent steps automatically.
Solution Approach 2:
The system maintains continuous useful action throughout the calibration process. The cascaded image registration process continuously processes images through coarse registration and then fine registration without interruption. The robotic arm continuously moves the head unit to capture calibration data across the entire field of view. This continuous automated processing eliminates the need for manual intervention at various stages, making the calibration process both highly automated and operationally simple.
Data Source
AI summary
An imaging system includes a housing assembly having a head unit configured to be at least partially directed towards a target site. An optical coherence tomography (OCT) module and a visualization module are located in the housing assembly and configured to respectively obtain OCT data and visualization data of the target site. The system includes a controller configured to generate a scanning pattern for a region of calibration selected in a calibration target. OCT data of the region of calibration is synchronously acquired. The controller is configured to obtain a projected two-dimensional OCT image of the region of calibration based on the OCT data, as an inverse mean-intensity projection. The controller is configured to register the projected two-dimensional OCT image to a corresponding view extracted from the visualization data, via a cascaded image registration process having a coarse registration stage and a fine registration stage.


