3D Imaging Volume Reduction for Biological Sample Analysis
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Solution Overview
Problem
Current volumetric sample imaging technologies face challenges in efficiently determining the axial bounds of biological samples, leading to oversampling in the Z-dimension, which increases computational resources and reduces throughput while maintaining data quality.
Innovation Solution
The method involves receiving 3D positional information of biological molecules within a sample, determining a reduced imaging volume based on this information, and directing the imaging instrument to image this smaller volume in subsequent cycles, using techniques such as bright field imaging or fluorescent imaging to generate contrast and minimize image acquisition in the Z-dimension.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large imaging volume is used to ensure complete sample coverage, then data quality is maintained, but imaging time increases and throughput decreases
Solution Approach 1:
The system performs a preliminary scanning cycle to acquire low-resolution or projection data before the main imaging process. This preliminary action identifies the actual axial bounds and signal-bearing regions of the sample, allowing subsequent high-resolution imaging to be focused only on relevant regions, thus maintaining data quality while reducing overall imaging time and increasing throughput
Solution Approach 2:
The imaging process is divided into distinct phases: a preliminary scanning phase to map sample boundaries, and a focused imaging phase to capture detailed data only within identified signal-bearing regions. This segmentation allows the system to optimize each phase separately, using minimal Z-sampling in the preliminary phase and concentrated high-resolution sampling in the focused phase
2Measurement precision
If a large imaging volume is used to ensure complete sample coverage, then data quality is maintained, but computational resources increase
Solution Approach 1:
The system extracts and identifies only the signal-bearing regions within the sample volume using the preliminary scanning data. By taking out and isolating these relevant regions from the entire sample volume, the system reduces the amount of data that needs to be processed in subsequent imaging cycles, thereby reducing computational resources while maintaining data quality in the regions of interest
3Reliability
If oversampling in the Z-dimension is performed, then complete sample coverage is achieved, but imaging time increases
Solution Approach 1:
The system dynamically adjusts the imaging strategy based on real-time feedback from preliminary scanning. Instead of using a fixed, conservative Z-sampling interval throughout the entire volume, the system adapts the sampling density to match the actual sample boundaries and signal distribution, using finer sampling only where signals are detected and coarser or no sampling in empty regions, thus reducing total imaging time while maintaining reliable coverage
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 allows for accurate identification of signal-bearing regions within the sample, reducing imaging time and computational burden while maintaining high data quality, thereby enhancing the throughput of automated high-throughput imaging systems.
Implementation Method 1
using techniques such as bright field imaging or fluorescent imaging to generate contrast
Data Source
AI summary
Provided herein are methods for minimizing Z-image acquisition comprising receiving a first set of three-dimensional (3D) positional information of a plurality of biological molecules within a sample, wherein the first set of 3D positional information is within a first imaging volume and based on a probing cycle of the sample in an imaging instrument, wherein the probing cycle comprises generating optical signals corresponding to at least some of the plurality of biological molecules; determining, based on the first set of 3D positional information, a second imaging volume that is less than the first imaging volume; and directing the imaging instrument to image the second imaging volume in at least one subsequent probing cycle of the sample.