Feature Boundary Pixel Detection in Array Scanners
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Solution Overview
Problem
Current methods for identifying feature boundary pixels in chemical arrays are inaccurate, leading to unreliable data analysis in genomics and proteomics applications, as they fail to effectively distinguish between feature and background pixels.
Innovation Solution
The method evaluates pixel signals by determining significant changes in amplitude between different parts of the signal, using a line of best fit with a slope greater than a threshold to indicate feature boundary pixels, and adjusts numerical evaluations accordingly to improve data accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to identify feature boundary pixels, then the process is simple, but the accuracy and reliability of data analysis deteriorates
Solution Approach 1:
The pixel signal is divided into multiple segments (first part and second part) along the scan direction. By segmenting the signal and comparing amplitude differences between segments, the method identifies feature boundary pixels more accurately without requiring complex external equipment.
Solution Approach 2:
The method performs preliminary evaluation of pixel signals during the scanning process itself, calculating amplitude differences and identifying feature boundary pixels before final data analysis. This preliminary action integrates boundary detection into the acquisition phase, improving overall accuracy without adding separate complex processing steps later.
2Reliability
If feature boundary pixels are not correctly identified, then data processing is faster, but the reliability of array data analysis deteriorates
Solution Approach 1:
The feature boundary pixel identification is performed continuously during the scanning process rather than as a separate post-processing step. The amplitude difference evaluation occurs for each pixel signal as it is acquired, maintaining continuous useful action and improving reliability without significant time loss.
Solution Approach 2:
The pixel signal itself contains the information needed for boundary identification through its amplitude variations. The method uses the signal's own characteristics (amplitude differences between segments) to identify boundary pixels, making the signal self-descriptive and eliminating the need for additional external measurement systems.
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 enhances the accuracy and reliability of data analysis by correctly identifying feature boundary pixels, thereby improving the interpretation of chemical array data in genomics and proteomics.
Implementation Method 1
For each pixel of a scan, a detector (e.g., photodetector such as a photomultiplier tube) may detect light emitted from the surface of a microarray, and output an analog signal line
Implementation Method 2
laser light may be used to excite fluorescent tags, generating a signal only in those spots on the biochip that have a target molecule and thus a fluorescent tag bound to a probe molecule
Data Source
AI summary
Methods for identifying feature boundary pixels are provided. In general, the subject methods involve evaluating a pixel signal to identify any difference in amplitude between a first part of the signal and a second part of the signal. If the difference is significant, the pixel signal may be indicated as a pixel representing a feature boundary. Also provided are systems and programming for performing the subject methods, and an array scanner containing these systems and programming.