Photometric Calibration for Automated Multispectral Imaging of Biological Samples

Over the past decade, there have been significant developments in the mechanisms for examination of biological and material samples. These developments exploit techniques in light microscopy to elucidate specific parts of cells and tissues, as well as inorganic particles. Sensor technology has progressed as well and modern charge-coupled devices (CCD) cameras are capable of achieving high spatial resolution and high sensitivity measurements of signals in the optical microscope. In this paper, we present a methodology for achieving photometric calibration of an automated multispectral imaging system targeted towards examination of biological samples. By acquiring spatial and spectral data simultaneously, multispectral imaging allows one to exploit physical connections between a particle’s morphology and its characteristic response to the optical spectrum. In composite biological material, the interpretation of the spectra is a complicated problem. This is because any light source and CCD camera used for data acquisition does not have a uniform illumination spectra and quantum efficiency, respectively, across the emitted light spectra. Fixed gain or exposure setting for a camera across all wavelengths does not allow efficient decoupling of the spectral signature of the biological particle from that of the camera’s imaging efficiency. To balance the spectral response across individual wavelengths, our method modulates the exposure duration for the CCD camera during image acquisition. We present an image similarity based method to calibrate the system. Five different distance metrics are compared and results presented by validating our approach by imaging particles in commercial blood standards. Photometric Calibration, Multispectral Imaging, Light Microscopy