Micro-camera Array Microscope Autofocus for Large Area Imaging
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Solution Overview
Problem
Current imaging systems face challenges in capturing high-resolution images over large areas due to limitations in lens design and maintaining focus across the entire field-of-view, leading to inefficiencies in data capture and processing.
Innovation Solution
The development of an imaging system that optimizes focus on features of interest within a camera array, using a moving mechanism to refocus micro-cameras and minimize out-of-focus areas, coupled with pattern illumination for enhanced contrast and feature detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If scanning-based approaches are used to capture high-resolution image data over large areas, then the imaging area can be extended into the multi-centimeter regime, but the imaging process becomes time-consuming due to sequential snapshot acquisition
Solution Approach 1:
The imaging system divides the large-area specimen into multiple sub-images captured by individual micro-cameras in parallel. Each micro-camera captures a portion of the specimen simultaneously, eliminating the need for sequential scanning and dramatically reducing total imaging time while maintaining high resolution across the entire multi-centimeter field of view.
2Measurement precision
If refocusing is performed at each unique position of the scanned specimen, then all regions can be brought into focus, but the process becomes extremely time-consuming
Solution Approach 1:
The system performs a preliminary coarse focus adjustment to bring the entire specimen into approximate focus before capturing images. This preliminary action eliminates the need for time-consuming iterative refocusing at each camera position, as the shallow depth of field of high-resolution lenses is compensated by ensuring the specimen plane is properly positioned relative to all micro-cameras simultaneously.
3Area of stationary object
If high-resolution lenses are designed to capture large areas, then the field of view can be extended, but the resolution deteriorates due to lens design limitations
Solution Approach 1:
Instead of using a single high-resolution lens that cannot maintain resolution across large areas, the system segments the imaging task across multiple micro-cameras with smaller fields of view. Each micro-camera captures high-resolution data over a limited area, and the individual images are computationally stitched together to form a high-resolution composite image of the entire multi-centimeter specimen, preserving resolution while extending the effective field of view.
4Reliability
If the entire image data is processed to ensure all areas are in focus, then complete coverage is achieved, but processing time and computational resources increase unnecessarily
Solution Approach 1:
The system applies focus evaluation and adjustment locally to regions containing features of interest rather than uniformly processing the entire image data. By identifying and prioritizing areas with relevant features, the system maintains reliable focus coverage where needed while skipping unnecessary processing in empty or non-critical regions, thereby significantly reducing computational load and processing time.
Data Source
AI summary
An imaging system is configured with an autofocus operation that refocuses multiple cameras of the imaging system on detected features of interest, instead of on the whole image of the sample. Focus measures are calculated on the detected features, and then aggregated to focus distances of actuator moving the camera array, the sample stage, or individual cameras based on a maximization of detected features to be in focus. After the refocus, the imaging system recaptures new images and analyzes features on the new images to generate statistical characterization of the sample based on the classification of the features.