FOV Reconstruction for Microscopic Imaging
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Solution Overview
Problem
In microscopic imaging, users face inefficiencies in examining samples with multiple objects across various depths due to redundant information and the challenge of identifying and analyzing multiple objects within a single Field Of View (FOV), leading to tedious processes and potential inaccuracies.
Innovation Solution
A method and system for reconstructing the FOV by determining the presence of single or multiple objects based on sharpness, generating optimal representations, and creating depth-based enhanced representations by retrieving and placing optimal images at corresponding depths, thereby reducing redundancy and improving analysis efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all images at each depth are examined for sample analysis, then complete information is obtained, but the examination process becomes tedious and time-consuming due to redundant information
Solution Approach 1:
The patent extracts only the essential and non-redundant information from multiple images by identifying representative images that capture the most important features of objects at different depths. This extraction process eliminates redundant data while preserving critical information, allowing users to analyze samples efficiently without examining every single image.
Solution Approach 2:
The system performs preliminary analysis of all captured images to identify and select representative images before presenting them to the user. This preliminary action includes detecting objects, determining their depths, and choosing the most informative images, so that users receive pre-processed, optimized image sets that require minimal further examination.
2Measurement precision
If multiple optimal images are selected for each object, then better representation is achieved, but the selection process becomes more complex and time-consuming
Solution Approach 1:
The patent applies local quality by selecting different numbers of optimal images for different objects based on their individual characteristics, such as size, shape, and depth position. Rather than applying a uniform selection criterion to all objects, the system adapts the selection process to each object's specific features, improving representation accuracy while maintaining manageable complexity.
3Ease of operation
If users examine images without depth information, then the process is simpler, but objects at different depths may be missed or misidentified
Solution Approach 1:
The patent introduces depth as an additional dimension in the image presentation by organizing selected images according to their depth information. This dimensional organization allows users to easily distinguish between objects at different depths while maintaining a simple graphical user interface. The depth-based arrangement naturally guides users through the sample structure without requiring complex operations.
Data Source
AI summary
Embodiments of present disclosure discloses system and method for reconstruction of FOV. Initially, presence of one of single object and distinct objects in FOV of image of sample comprising one or more objects is determined based on sharpness of one or more objects. A single optimal representation of FOV may be generated when presence of single object is determined. At least one of single optimal representation and a depth-based enhanced representation of FOV may be generated when presence of distinct objects is determined. For generating depth-based enhanced representation, one or more first optimal images associated with each of distinct objects in FOV may be retrieved. An optimal representation of each of distinct objects is generated based on corresponding one or more first optimal images. Further, optimal representation of each of distinct objects is placed at corresponding optimal depth associated with respective distinct object to generate depth-based enhanced representation.