Multi-Snapshot Imaging for Chromatographic Peak Analysis

James Hopgood, Matthew Connelly, Barry McHoull, Darren Troy

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: Snapshot imaging has several advantages in automated gel electrophoresis compared with the finish-line method in capillary electrophoresis; this comes at the expense of resolution. A novel signal processing algorithm is proposed enabling a multi-snapshot imaging (MSI) modality whose objective is to substantially improve resolution. MSI takes multiple-captures in time as macromolecules are electrophoresed. Peaks from latter snapshots have high resolution but low signal-to-noise ratio (SNR), while earlier snapshots have low resolution but high SNR. Methods: Signals at different capture-times are related by a scale-in-separation, shift-in-separation, and amplitude gain. The proposed method realigns the multiple captures using least-squares and fuses them. The algorithm accounts for the partial waveforms observed as the chromatic peaks exit the sensor’s field-of-view. Results: MSI improves resolution by approximately 10% on average per minute of additional electrophoresis. Conclusions: Comprehensive analysis of the resolution are quantified on several datasets demonstrate the effectiveness of MSI. Significance: MSI can double the resolution compared with traditional snapshot imaging over a typical set of captures.
Original languageEnglish
Pages (from-to)119-129
JournalIEEE Transactions on Biomedical Engineering
Volume66
Issue number1
DOIs
Publication statusPublished - 12 Apr 2018

Keywords

  • image resolution
  • imaging
  • signal resolution
  • standards
  • shape
  • DNA
  • Signal processing algorithms
  • signal processing and modelling
  • chromatography
  • snapshot imaging
  • finish-line
  • parameter estimation
  • Fusion

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