Blood Image Plane Analysis for Faster Cell Parameter Detection
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Solution Overview
Problem
Existing blood sample analysis methods, particularly for determining cell parameters, are lengthy, resource-intensive, and require advanced equipment, making them inefficient and costly.
Innovation Solution
A blood analyser system that obtains image data of a prepared blood sample, selects and characterizes images from different planes, determines cell regions, and calculates cell parameters using a stack of images associated with varying heights along the z-axis, allowing for faster and more accurate cell classification and counting without the need for extensive dilution or specialized equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional blood sample analysis methods are used, then cell parameters can be determined, but the analysis process is lengthy and requires numerous preparation steps and advanced equipment
Solution Approach 1:
The patent replaces complex mechanical and chemical analysis systems with an optical imaging system. Instead of using flow cytometers, Coulter counters, or other advanced laboratory equipment, the invention uses a camera to capture images of blood cells and processes these images computationally to determine cell parameters. This substitution of mechanical/chemical systems with optical-digital systems enables rapid analysis without specialized equipment.
Solution Approach 2:
The patent creates digital copies (images) of blood cells using a camera system. These image copies contain sufficient information to determine cell parameters such as size, shape, and morphology. By working with digital replicas rather than physical samples, the system eliminates the need for complex preparation and analysis equipment while maintaining analytical capability.
2Measurement precision
If extensive dilution is performed in conventional analysis, then cell parameters can be measured, but the process requires more chemicals, time, and resources
Solution Approach 1:
The patent extracts only the essential visual information needed for cell parameter determination from the blood sample images. Instead of performing extensive dilution and chemical processing to isolate and measure cell properties, the system directly captures and analyzes the optical characteristics of cells in the image data, eliminating the need for chemical reagents and dilution steps.
Solution Approach 2:
The blood cells themselves provide the measurement information through their natural optical properties in the captured images. The cells' morphology, size, and other parameters are directly observable in the image data without requiring external chemicals or complex preparation. The system uses the cells' inherent characteristics to perform self-measurement.
3Productivity
If single-plane image analysis is used, then processing is simpler, but cell parameter determination lacks accuracy and detail
Solution Approach 1:
The patent transitions from two-dimensional single-plane imaging to three-dimensional multi-plane imaging. By capturing images at multiple focal planes along the z-axis, the system obtains depth information and complete cell morphology data. This dimensional expansion enables accurate determination of cell parameters while maintaining processing efficiency through automated image stack analysis.
Data Source
AI summary
A blood analyser and related methods, in particular a method of analysing a blood sample is disclosed. The blood analyser comprises a memory, an interface, and one or more processors. The blood analyser is configured to obtain image data of a prepared blood sample; select a first image associated with a first image plane of the prepared blood sample from the image data; characterize the first image, wherein the characterization of the first image comprises to determine a first set of cell regions belonging to the first image plane; select a first distal image associated with a first distal image plane on a distal side of the first image plane, and determine a first distal set of distal cell regions associated with the first set of cell regions; and determine a first cell parameter for each cell region of the first set of cell regions based on the first distal set of distal cell regions.