Slide Imaging Focus Extrapolation for Debris
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing slide imaging technologies face challenges in achieving optimal focus during single-pass scanning, particularly when dealing with debris, pen marks, and varying tissue densities, which can lead to out-of-focus errors and increased scanning time.
Innovation Solution
An apparatus and method for slide imaging that includes an optical system, a processor, and memory, which captures multiple images at different focus distances within a region of interest, identifies a focus pattern, and extrapolates the optimal focus distance for subsequent image capture, ensuring accurate focus despite obstacles or varying sample densities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If single-pass scanning is used to digitize slides, then scanning time is reduced, but focus accuracy deteriorates due to debris, pen marks, and varying tissue densities causing wrong z-reference plane selection
Solution Approach 1:
The system performs preliminary actions by capturing multiple images at different z-positions before final image selection. It captures a first image at an initial z-position, then captures additional images at different z-positions based on detected focus patterns, ensuring proper focus is established before completing the scanning process
Solution Approach 2:
The system uses feedback mechanisms by analyzing captured images to detect focus patterns caused by debris or pen marks, then adjusting the z-position based on this feedback. The processor determines whether to adjust z-position by comparing focus metrics and using machine learning models to predict optimal focus positions
2Measurement precision
If multiple images are captured at different z-positions to ensure focus accuracy, then focus quality improves, but scanning time increases
Solution Approach 1:
The system applies partial action by capturing multiple images only in regions where focus issues are detected rather than uniformly across the entire slide. It uses machine learning models to identify regions of interest where debris or pen marks are present, then selectively captures additional images only in those areas
Solution Approach 2:
The system segments the scanning process into different phases: initial rapid scanning to identify focus issues, targeted additional imaging only in problematic regions, and final image composition. This segmentation allows most of the slide to be scanned quickly while dedicating additional time only where necessary
3Measurement precision
If z-position is adjusted frequently to accommodate debris or pen marks, then focus accuracy improves, but device complexity increases
Solution Approach 1:
The system replaces complex mechanical z-position adjustment mechanisms with computational methods. It uses machine learning models and image analysis algorithms to predict optimal z-positions and calculate focus adjustments, substituting mechanical complexity with software-based solutions
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Aspects of present disclosure relate to slide imaging. An exemplary apparatus for real time image generation includes at least an optical system, a slide port configured to hold a slide, an actuator mechanism mechanically connected to a mobile element, a user interface comprising an input interface and an output interface, at least processor configured to: receive at least a region of interest; capture, using the at least an optical system, a first image of the slide at a first position within the at least a region of interest; identify a focus pattern as a function of the first image and the first position; extrapolate a focus distance for a second position as a function of the focus pattern; and capture, using the at least an optical system, a second image of the slide at a second position and at the focus distance.