Optical coherence tomography angiography (OCTA) is a well-established retinal imaging modality that is emerging as a fast, non-invasive alternative to fluorescence angiography for assessment of corneal injury and neovascularization caused by chemical injuries, infections, and other sources of corneal damage. OCTA algorithms typically perform operations on multiple scans, or frames, at the same location to identify flowing vasculature. In this work, we describe a novel single-frame algorithm that relies on common image processing operations, allowing for broad application to various OCT systems, as well as reduced acquisition and computation times. We also show the potential of a multi-frame approach, based on the same principle, that allows for enhanced discrimination between flowing and static anatomical features. To demonstrate the capability of our approach, we processed the same image stack with our single-frame and multi-frame algorithms along with other angiography algorithms, such as phase variance, speckle variance, and complex differential variance and found that our algorithms had higher estimated signal-to-noise ratios (SNR) and lower computation times. We applied our algorithms to quantifying corneal neovascularization (CoNV) in a murine model of corneal burn injury through semi-automated measurement of vessel area and compared them to the gold standard of fluorescein angiography. This work provides strong evidence for the power of the single-frame algorithm and its multi-frame variant, as well as the potential of OCTA for quantification of corneal pathology beyond the standard fluorescein angiography approach allowing for more accurate monitoring and staging of corneal injury and wound healing.