Digital Tomosynthesis Clutter Removal via 2D-3D Registration
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Solution Overview
Problem
Current medical imaging technologies, such as 2D fluoroscopy and cone beam CT, face challenges in providing precise intraoperative guidance due to clutter from background anatomy, high radiation doses, and significant interruption to clinical workflow, especially during repeated acquisitions or procedures requiring multiple 3D image alignments.
Innovation Solution
The development of a digital tomosynthesis technique using 2D to 3D registration methods allows for the creation of patient-specific, curved, or non-planar imaging planes within a standard fluoroscopy system, enabling the removal of clutter and minimizing radiation exposure by aligning 3D data with 2D images for enhanced visualization of clinically relevant structures during surgical procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If cone beam CT is used for 3D imaging, then imaging completeness is improved, but set-up time increases significantly
Solution Approach 1:
The patent segments the 3D imaging process into multiple 2D tomosynthesis acquisitions taken at different angles during normal fluoroscopy workflow, rather than requiring a single comprehensive CBCT scan. This allows 3D information to be built incrementally without interrupting surgical flow.
Solution Approach 2:
The system performs preliminary 2D tomosynthesis acquisitions during routine fluoroscopy before 3D reconstruction is needed. The 3D volume is constructed from these pre-acquired images, eliminating the need for separate CBCT set-up time when 3D imaging is required.
2Loss of information
If multiple CBCT acquisitions are performed, then imaging completeness is improved, but radiation dose increases significantly
Solution Approach 1:
The patent acquires more 2D tomosynthesis images than strictly necessary for 2D diagnosis, using the excess images for 3D reconstruction. This partial use of acquired data eliminates the need for separate CBCT scans, reducing overall radiation exposure while still achieving complete 3D imaging when needed.
3Productivity
If 2D fluoroscopy is used for real-time imaging, then acquisition speed is improved, but image precision deteriorates due to background clutter
Solution Approach 1:
The patent transitions from 2D fluoroscopy to 3D tomosynthesis reconstruction, adding a depth dimension to the imaging. This allows clinicians to view structures in their true spatial relationships without superimposed background anatomy, improving precision while maintaining real-time capability.
Solution Approach 2:
The system uses 2D tomosynthesis images as an intermediary step between real-time fluoroscopy and full 3D CBCT. These intermediate images provide sufficient 3D information for many applications without requiring complete CBCT reconstruction, maintaining speed while improving precision.
4Measurement precision
If dedicated diagnostic tomosynthesis equipment is used, then image quality is improved, but device complexity increases
Solution Approach 1:
The patent makes the standard fluoroscopy C-arm system multi-functional by adding software capabilities to perform 2D tomosynthesis and 3D reconstruction. This eliminates the need for separate dedicated tomosynthesis equipment, reducing device complexity while maintaining improved image quality through 3D visualization.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables minimal disruption to clinical workflow, reduces radiation dose, and provides precise, clutter-free images of anatomical features, improving surgical guidance and reducing the need for contrast agents by allowing for real-time visualization of soft tissues with enhanced clinical relevance.
Implementation Method 1
obtain a plurality of images through a subject to be imaged
Data Source
AI summary
An image generation method is described, comprising obtaining a plurality of 2D images through an object to be imaged, obtaining a 3D image data set of the object to be imaged, and registering the 2D images with the 3D image data set. The method then further includes defining an image reconstruction plane internal to the object, being the plane of an image to be reconstructed from the plurality of 2D images. Then, for a pixel in the image reconstruction plane, corresponding pixel values from the plurality of 2D images are mapped thereto, and the mapped pixel values are combined into a single value to give a value for the pixel in the image reconstruction plane. Another aspect of the method provides for clutter removal from the image. In a medical imaging context this can provide for “de-boned” images, allowing soft tissue to be more clearly seen.