A method for cytometric image parameterization

New advances in wide-angle cytometry have allowed researchers to obtain micro- and nano-structural information from biological cells. While the complex two-dimensional scattering patterns generated by these devices contain vital information about the structure of a cell, no computational analysis methods have been developed to rapidly extract this information. In this work we demonstrate a multi-agent computational pipeline that is able to extract features from a two-dimensional laser scattering image, cluster these features into spatially distinct regions, and extract a set of parameters relating to the structure of intensity regions within the image. This parameterization can then be used to infer medically relevant properties of the scattering object.