| 摘要 |
Hardware and software components are configured to image-process centroid data as if they were profile data to discover biological features. Proper mass/charge bin size are determined to raster centroid data into LC/MS images. To correct for the decrease in precision, the LC/MS images are re-evaluated in view of the original centroid data. Peak detection from the binned image is refined by re-considering the corresponding centroid data through cluster analysis. Additionally, some peaks that were merged through processing may be resolved into individual peaks by identifying more than one significant cluster masked by a peak from the binned image.
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