'Columbia University Libraries/Information Services'
Doi
Abstract
We present a variant on the robust-principal component analysis (RPCA) algorithm, called frequency constrained RPCA (FC-RPCA), for selectively segmenting dynamic phenomena that exhibit spectra within a user-defined range of frequencies. The algorithm lacks subjective parameter tuning and demonstrates robust segmentation in datasets containing multiple motion sources and high amplitude noise. This algorithm was designed to be used with time-lapse Optical Coherence Tomography (OCT) datasets that capture sub-resolution motion. Specifically demonstrated for cilia
