Compressed Pixel Mapping for Faster Sample ROI Detection
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Solution Overview
Problem
Scanning large areas with high-magnification microscopes is time-consuming due to the small field of view and the need for multiple image captures and focus adjustments, and systems with only high-magnification objectives lack flexibility in field of view adjustment.
Innovation Solution
A method and device that capture and process digital image data sets to form compressed digital representations, identifying regions of interest based on pixel values without requiring spatial details, reducing data processing and bandwidth needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-magnification microscope objective is used to scan large areas, then imaging resolution is improved, but scanning time increases significantly
Solution Approach 1:
The patent divides the large-area sample into multiple smaller fields of view that are captured sequentially. Instead of attempting to capture the entire large area at high magnification simultaneously, the system segments the scanning task into multiple manageable positions, capturing images at each position and then compositeing them into a complete high-resolution map of the entire sample area.
Solution Approach 2:
The patent implements a two-stage scanning approach where a preliminary low-magnification scan is performed first to identify regions of interest (ROIs) containing potential objects. Based on this preliminary information, the system then performs a second high-magnification scan only at the identified ROI positions, avoiding the time-consuming task of high-magnification scanning across the entire large area.
2Productivity
If microscope objective is changed to lower magnification to increase field of view, then scanning speed is improved, but imaging resolution deteriorates
Solution Approach 1:
The patent implements a dynamic magnification system that automatically adjusts the microscope objective magnification based on the detected content. The system transitions between low magnification (for rapid overview scanning) and high magnification (for detailed imaging of specific regions) depending on whether objects are detected, thereby optimizing both scanning speed and resolution according to the actual requirements of each scanning phase.
Solution Approach 2:
The patent changes the magnification parameter of the microscope objective dynamically during the scanning process. The system starts with low magnification to quickly cover large areas, then switches to high magnification only when and where objects are detected, thereby achieving both fast scanning capability and high-resolution imaging where needed.
3Measurement precision
If high-magnification microscope objective is used, then detailed imaging capability is improved, but field of view decreases
Solution Approach 1:
The patent segments the large sample area into multiple smaller fields of view that can be captured at high magnification. By dividing the overall scanning task into multiple positions, the system can maintain high detailed imaging capability at each position while collectively covering a large total area through the combination of multiple segmented images.
Solution Approach 2:
The patent performs a preliminary low-magnification scan to identify which specific regions require detailed high-magnification imaging. This preliminary action allows the system to limit high-magnification scanning only to necessary regions, thereby maintaining detailed imaging capability where needed while avoiding the waste of time and resources on areas that do not contain objects of interest.
4Measurement precision
If multiple focus adjustments are made during scanning to produce detailed images, then image quality is improved, but scanning time increases
Solution Approach 1:
The patent performs focus adjustments and high-quality image capture only at identified regions of interest rather than at every scanning position. The preliminary low-magnification scan identifies where objects are located, and subsequent focus adjustments are made only at those specific positions, thereby maintaining high image quality for objects while minimizing the time spent on focus adjustments across the entire large area.
Data Source
AI summary
The present disclosure relates to a method (40) and a device (10) for identifying a region of interest in a sample (192). The method (40) comprising: capturing (S400), by an image sensor (150), a plurality of digital image data sets (300), each digital image data set comprising pixels and pertaining to a position of a plurality of positions of the sample; for each digital image data set: forming (S402) a set of combined pixels, each combined pixel having a pixel value, and wherein each pixel value is determined based on at least one of an intensity value and a color value pertaining to a subset of pixels of the digital image data set, and forming (S404) a compressed digital representation comprising the set of combined pixels; arranging (S406) the compressed digital representations in a data structure, thereby forming a common compressed digital representation (350) of the sample (192), wherein the data structure for each compressed digital representation includes information pertaining to a position of the plurality of positions of the sample of the digital image data set associated with the compressed digital representation; and identifying (S408) a region of interest of the sample (192) based on a pixel value of the common compressed digital representation.