Charged Particle Beam Imaging With Drift-Aware Image Integration
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Solution Overview
Problem
Charged particle beam apparatuses, such as SEMs, face challenges in maintaining image quality due to random noise suppression techniques that also degrade sharpness, caused by factors like sample drift, contamination, and environmental disturbances, requiring lengthy trial-and-error processes to optimize imaging conditions.
Innovation Solution
A charged particle beam apparatus with an imaging device and a computer that classifies images into deteriorated and non-deteriorated categories, integrates only non-deteriorated images, and uses a database to store and display relevant data for user correction, employing machine learning to evaluate image quality and suppress noise while maintaining sharpness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images are integrated to suppress random noise, then the signal-to-noise ratio is improved, but the image sharpness deteriorates due to drift and instability during prolonged scanning
Solution Approach 1:
The patent applies preliminary action by evaluating image quality indicators (sharpness, noise level, drift) for each candidate image before integration. The image selection unit pre-screenes images to determine whether to include them in the integrated image, preventing deterioration before it occurs. This is implemented through the image quality evaluation unit that assesses each image's suitability for integration based on predetermined criteria.
Solution Approach 2:
The patent implements feedback through the image quality evaluation unit that continuously monitors and assesses the quality of each acquired image. The evaluation results (sharpness, noise, drift metrics) feed back to the image selection unit, which adjusts the integration process accordingly. This closed-loop feedback mechanism ensures that only high-quality images contribute to the final integrated image, maintaining both sharpness and noise suppression.
2Quantity of substance
If the scanning time is extended to collect more detection signals, then the dynamic range increases, but the stability of the SEM and sample decreases over time
Solution Approach 1:
The patent applies preliminary action by evaluating image quality indicators (sharpness, noise level, drift) for each candidate image before integration. The image selection unit pre-screenes images to determine whether to include them in the integrated image, preventing deterioration before it occurs. This is implemented through the image quality evaluation unit that assesses each image's suitability for integration based on predetermined criteria.
Solution Approach 2:
The patent implements feedback through the image quality evaluation unit that continuously monitors and assesses the quality of each acquired image. The evaluation results (sharpness, noise, drift metrics) feed back to the image selection unit, which adjusts the integration process accordingly. This closed-loop feedback mechanism ensures that only high-quality images contribute to the final integrated image, maintaining both sharpness and noise suppression.
3Manufacturing precision
If trial and error is performed to find optimal imaging conditions, then the image quality improves, but the operation time increases and sample damage occurs
Solution Approach 1:
The patent applies self-service by implementing an automated image quality evaluation and selection system that operates without user intervention. The image quality evaluation unit automatically assesses each image's sharpness, noise level, and drift, while the image selection unit autonomously determines which images to include in the integration. This eliminates the need for manual trial and error, reducing operation time and minimizing sample exposure to beam damage.
Solution Approach 2:
The patent implements feedback through the image quality evaluation unit that continuously monitors and assesses the quality of each acquired image. The evaluation results (sharpness, noise, drift metrics) feed back to the image selection unit, which adjusts the integration process accordingly. This closed-loop feedback mechanism ensures that only high-quality images contribute to the final integrated image, maintaining both sharpness and noise suppression.
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 effectively prevents image quality deterioration, enhances sharpness, and reduces sample damage and operational time by identifying and correcting image quality issues, resulting in high S/N ratio images.
Implementation Method 1
a scanning electron microscope is a device that uses an electron beam as the charged particle beam and forms an image from detection signals such as secondary electrons and reflected electrons generated by scanning the sample
Implementation Method 2
forms an image from detection signals such as secondary electrons and reflected electrons generated by scanning the sample with a finely focused electron beam (probe)
Data Source
AI summary
With respect to a charged particle beam apparatus, provided is a technology capable of preventing a deterioration in image quality of a captured image. The charged particle beam apparatus includes an imaging device that irradiates a sample with a charged particle beam and forms an image from information of the sample and a computer. The computer stores each of images (scanned images) obtained by scanning the same area multiple times, classifies each of images into an image including a deteriorated image and an image not including the deteriorated image, and stores a target image obtained by performing image integration from the image not including the deteriorated image. The charged particle beam apparatus includes a database that stores data such as information obtained from an imaging device including the scanned image, classification results, and the target image. The charged particle beam apparatus obtains a target image having a high S/N and sharpness in which random noise is suppressed and a deterioration in image quality is prevented by performing the image integration on the scanned image that does not include the selected deteriorated image among the scanned images.