Fluorescence Signal Differential Compression for Cloud Flow Cytometry
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Solution Overview
Problem
The increasing number of dimensions in data acquired by multi-coloring fluorescence signals in spectral-type flow cytometers leads to significant data transfer times and storage costs when analyzing samples in a cloud environment.
Innovation Solution
The implementation of data reduction methods such as lexicographic compression, entropy coding, and statistical prediction, combined with the generation and use of differential data to compress and decompress data efficiently, reduces the data amount and storage requirements by leveraging the characteristics of sample groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multi-coloring fluorescence signals is used to enable detailed analysis, then measurement precision is improved, but data amount increases significantly
Solution Approach 1:
The patent extracts and utilizes the spectral characteristics of fluorescent dyes by acquiring measurement spectra across multiple wavelength regions. Instead of treating all data points equally, the invention identifies and extracts the distinctive spectral signatures of each fluorescent dye, using only the necessary spectral information for identification and quantification, thereby reducing redundant data while maintaining analysis precision.
Solution Approach 2:
The patent transforms the raw spectral data by changing the parameter representation from individual wavelength intensity values to spectral feature parameters such as peak positions, peak intensities, and spectral shapes. This parameter transformation reduces the dimensionality of the data while preserving the essential information needed for distinguishing and quantifying multiple fluorescent dyes.
2Productivity
If data is transferred to Cloud environment for analysis, then analysis capability is improved, but data transfer time increases
Solution Approach 1:
The patent extracts and transfers only the essential spectral feature parameters to the Cloud environment rather than transferring complete raw spectral data. By identifying and transmitting only the critical parameters needed for analysis (such as spectral peaks and key wavelength regions), the invention significantly reduces data transfer time while maintaining the Cloud's analytical capabilities.
3Ease of operation
If data is stored in Cloud environment, then storage accessibility is improved, but storage cost increases
Solution Approach 1:
The patent extracts and stores only the essential spectral feature parameters in the Cloud environment rather than storing complete raw spectral datasets. By identifying and retaining only the critical parameters needed for future analysis and reference, the invention significantly reduces storage requirements and associated costs while maintaining easy accessibility to the essential measurement information.
Data Source
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AI summary
To reduce a data amount. An information processing system according to an embodiment includes an excitation light source (100) that irradiates a respective plurality of samples belonging to a sample group with excitation light, a measurement unit (142) that measures fluorescence generated by irradiation of the samples with the excitation light, and an information processing unit (2) that generates differential data based on a difference between similar fluorescence signals among fluorescence signals based on the fluorescence measured for the respective samples.