Tomographic Reconstruction Using SEM Constraints
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Solution Overview
Problem
Tomographic imaging faces inaccuracies and artifacts due to the 'missing wedge' and 'local tomography' problems, where incomplete angular ranges of input images lead to significant inaccuracies and sensitivity to noise, resulting in sub-optimal reconstructions.
Innovation Solution
The method employs three-dimensional Scanning Electron Microscopy (SEM) imagery to constrain the solution space of tomographic reconstructions, ensuring consistency with SEM pixel values, using iterative mathematical techniques and regularization functions to filter out unrealistic solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional tomographic reconstruction is performed with limited angular input images, then the reconstruction process can be completed, but the resolution and fidelity are extremely sensitive to noise and produce significant artifacts
Solution Approach 1:
The method performs preliminary action by acquiring three-dimensional SEM imagery of the specimen before tomographic reconstruction. This pre-acquired structural information is then used to constrain the solution space during reconstruction, providing a reference framework that guides the reconstruction algorithm to produce more accurate and noise-resistant results despite limited angular input images.
Solution Approach 2:
The method implements feedback by using the pre-acquired three-dimensional SEM imagery to continuously constrain and guide the tomographic reconstruction process. The SEM data serves as a reference that feedbacks into the reconstruction algorithm, allowing it to adjust and refine the solution to remain consistent with known specimen structures, thereby improving fidelity and noise robustness.
2Ease of operation
If the angular range of input images is limited due to specimen holder tilt range or apparatus obscuration, then the imaging process can be completed with current apparatus, but the missing wedge problem causes significant inaccuracies in the tomogram
Solution Approach 1:
The method introduces three-dimensional SEM imagery as an intermediary element that mediates between the limited angular tomographic input images and the final reconstruction. This intermediary provides additional structural information that compensates for the missing wedge problem, allowing accurate reconstruction despite the limited angular range imposed by current apparatus constraints.
3Measurement precision
If mathematical constraints are applied to curtail the solution space, then dud solutions are filtered out, but the complexity of the reconstruction process increases
Solution Approach 1:
The complexity is managed through preliminary action by acquiring the three-dimensional SEM imagery before reconstruction. This pre-prepared constraint data structures the solution space in advance, making the subsequent constrained reconstruction process more efficient and manageable despite the increased mathematical complexity required to incorporate these constraints.
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 enhances the fidelity and resolution of tomographic images by eliminating unrealistic solutions and improving the robustness of reconstructions, particularly addressing the 'missing wedge' and 'local tomography' issues.
Implementation Method 1
Directing a beam of radiation through the specimen and onto a detector, thereby generating an image of the specimen
Data Source
AI summary
Methods of investigating a specimen using tomographic imaging include directing a beam of radiation through a specimen and onto a detector, thereby generating an image of the specimen. The directing is repeated for different specimen orientations relative to the beam, thereby generating a corresponding set of images. An iterative mathematical reconstruction technique is used to convert the images into a tomogram. The reconstruction is mathematically constrained to curtail a solution space using three-dimensional SEM imagery of at least a part of the specimen that overlaps the tomogram by requiring iterative results of the reconstruction to be consistent with pixel values derived from the SEM imagery.