METHODS FOR HYPERSPECTRAL MICROSCOPE CALIBRATION AND SPECTRA NORMALIZATION FROM IMAGES OF BACTERIA CELLS

摘要

Hyperspectral microscope images (HMIs) have previously shown promise as a means for rapid and early detection of foodborne bacteria at the cellular level. System calibration and data normalization are critical for comparing information obtained from HMIs collected with multiple instruments and system parameters. Here, we implement a wavelength and radiometric calibration for spectral data obtained from a hyperspectral microscope, assess the spatial uniformity of HMIs, and show the need to normalize data from single-cell regions of interest (ROIs). A hyperspectral microscope with a tungsten halogen light source, acousto-optical tunable filter, and electron multiplying camera with variable gain and exposure time settings were used. HMIs were collected at additional gain settings of 0%, 1.6%, 3.5%, and 5.1% along with ten exposure time settings between 100 and 1000 ms with both calibration lamps. Wavelength peak shift started to occur at an exposure time of 600 ms for 1.6% gain, at 400 ms for 3.5% gain, and at 200 ms for 5.1% gain. HMIs of E. coli, Salmonella Typhimurium, and Staphylococcus sciuri cells were collected to assess spectral data normalcy and the need for preprocessing spectra from single bacteria cells. Spatial characteristics of cells were assessed by HMIs of a glass slide with a micrometer for determining pixel size from the field of view. HMIs were preprocessed by normalizing cell spectra to the light source and applying multiplicative scatter correction. Data normalcy was assessed on both the raw and preprocessed data sets. Preprocessing the data was found to reduce the cell-to-cell variation associated with a single-cell ROI method, while outliers were detected and verified through HMIs as physically different from other cells.