Shimadzu has been granted a patent for an analyzer that performs qualitative and quantitative analysis of sample components. It features a peak detection unit that identifies peaks in chromatograms or spectra, acquires peak information, and generates confidence values for detection, alongside a display unit for presenting target components. GlobalData’s report on Shimadzu gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Shimadzu, Image segmentation techniques was a key innovation area identified from patents. Shimadzu's grant share as of July 2024 was 39%. Grant share is based on the ratio of number of grants to total number of patents.
Analyzer for qualitative and quantitative analysis of samples
The granted patent US12072323B2 describes an advanced analyzer designed for the qualitative and quantitative analysis of target components in samples through the acquisition of chromatograms or spectra. The analyzer features a peak detection unit that identifies peaks corresponding to target components and gathers peak information, including confidence information that indicates the certainty of peak detection. This unit employs a machine learning-based model trained on multiple chromatograms or spectra, allowing it to accurately determine the start and end points of detected peaks. Additionally, the display processing unit presents a list of target components alongside their corresponding confidence information, enabling users to assess the reliability of the detected peaks.
Further enhancements to the analyzer include the ability to utilize prior information about target components for peak detection and a quantitative analysis unit that calculates quantitative values for the identified components. The display processing unit can compare confidence information against a predetermined threshold, visually distinguishing between peaks with varying levels of confidence. It can also sort the list based on confidence levels and display multiple confidence data points for each peak across several chromatograms. This comprehensive approach aims to improve the accuracy and usability of analytical results, making it a valuable tool in various scientific and industrial applications.
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