Massively parallel data processing for quantitative total flow imaging with optical coherence microscopy and tomography

Published: 1 August 2017| Version 1 | DOI: 10.17632/32kwbxyvj9.1
Marcin Sylwestrzak, Daniel Szlag, Paul J. Marchand, Ashwin S. Kumar, Theo Lasser


Abstract We present an application of massively parallel processing of quantitative flow measurements data acquired using spectral optical coherence microscopy (SOCM). The need for massive signal processing of these particular datasets has been a major hurdle for many applications based on SOCM. In view of this difficulty, we implemented and adapted quantitative total flow estimation algorithms on graphics processing units (GPU) and achieved a 150 fold reduction in processing time when compared to a f... Title of program: CudaOCMproc Catalogue Id: AFBT_v1_0 Nature of problem Speed up of data processing in optical coherence microscopy Versions of this program held in the CPC repository in Mendeley Data AFBT_v1_0; CudaOCMproc; 10.1016/j.cpc.2017.03.008 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)



Optics, Computer Hardware, Software, Programming Language, Computational Physics