ABSTRACT
Our laboratories have recently developed a flow-through imaging photometer to characterize and classify fluorescent particles between 3 and 47 µm in size. The wide aperture of the objective lens (0.7 NA) required for measuring spectral fluorescence of single particles restricts the depth of field, such that a large sample volume results in many particles that are out of focus. Here, we describe numerical methods for determining the size of these objects, regardless of their distance from the focal plane, using image processing and multivariate calibration. An intensity profile is extracted from the images and is used as the input for a variety of calibration methods, including partial least squares, neural networks, and support vector machines. The capabilities of these methods are examined to establish the best method for particle sizing that is independent of focus. We found that support vector machines provided the best results, with size estimation error of ±3.1 µm.
