3D Imaging System Using Pre-Scan Segmentation to Reduce Data Volume
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Solution Overview
Problem
Current methods for imaging three-dimensional objects, particularly biological cells, are time-consuming and inefficient, generating large amounts of irrelevant data due to the need to scan entire volumes, which slows down imaging and increases costs.
Innovation Solution
A method and system that utilize pre-scanning with a lower magnification objective to identify x-y coordinates and z-height of objects, followed by high-resolution scanning using a higher magnification objective only where objects are present, reducing data volume and scan time by focusing on specific areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire matrix volume is scanned using high magnification objective to image three-dimensional objects, then imaging precision is improved, but scan time and data volume increase significantly
Solution Approach 1:
The imaging process is divided into two segments: a pre-scan phase using low magnification objective to identify object locations and a main scan phase using high magnification objective to capture detailed images only at identified locations. This segmentation allows the system to maintain high imaging precision while dramatically reducing scan time by avoiding unnecessary scanning of empty matrix regions.
Solution Approach 2:
A pre-scan operation is performed before the main imaging process to identify the three-dimensional locations of objects within the matrix. This preliminary action provides location information that guides the subsequent high magnification scanning, ensuring that time-consuming detailed imaging is performed only where objects are present, thus reducing overall scan time while maintaining precision.
2Measurement precision
If the entire matrix volume is scanned using high magnification objective to image three-dimensional objects, then imaging precision is improved, but data volume increases significantly
Solution Approach 1:
The imaging process is divided into two segments: a pre-scan phase using low magnification objective to identify object locations and a main scan phase using high magnification objective to capture detailed images only at identified locations. This segmentation allows the system to maintain high imaging precision while dramatically reducing data volume by avoiding unnecessary scanning of empty matrix regions.
Solution Approach 2:
The patent extracts only the relevant portions of the matrix that contain objects for detailed imaging. By using pre-scan data to identify object locations, the system extracts and images only the necessary sub-volumes, discarding the vast amount of empty matrix space, thus reducing data volume while preserving imaging precision for actual objects.
3Loss of time
If pre-scanning is performed using low magnification objective followed by high magnification scanning, then scan time is reduced, but device complexity increases
Solution Approach 1:
The microscope system is configured to perform multiple functions using the same hardware platform: low magnification pre-scanning, high magnification detailed imaging, and automated coordinate transformation. This multi-functionality reduces the need for separate specialized devices while achieving time reduction benefits, as the system can switch between objectives and modes without requiring entirely separate imaging systems.
4Productivity
If automated imaging is implemented with coordinate transformation, then productivity is improved, but device complexity increases
Solution Approach 1:
The system uses feedback from the pre-scan operation to automatically adjust and transform coordinates for the main scanning process. The processor receives location data from low magnification imaging, performs coordinate transformations, and uses this information to guide high magnification scanning. This automated feedback loop improves productivity by eliminating manual positioning while the software-based coordinate transformation keeps hardware complexity manageable.
Data Source
AI summary
Certain configurations are described of methods and systems that can be used to image three-dimensional objects such as biological cells, biological tissues or biological organisms. The methods and systems can image the three-dimensional objects at reduced imaging times and with reduced data volumes.