Image cytometry is an emerging technique that uses digital images to characterize individual cells flowing at high-speeds through microchannels. These images can be used purely for characterization purposes, to inform upon real-time decision making, or for generating statistics on large populations of cells. Analyses are often utilized to extract size, shape, color, opacity, elasticity, and/or kinematic information such as displacement, speed, or acceleration. High-speed machine vision systems also enable the ability to perform real-time system feedback based on the information contained within the images, allowing users to filter, destroy, and/or sort specific cells. In recent years, state-of-the-art imaging hardware (together with low-level software) has allowed researchers to push the limits on the throughput of image cytometry, where systems are now capable of streaming images at frame rates between 10 and 100 kHz and perform decisions at real- or near-real time.