Premium
Optical coherence tomography angiography for mapping cerebral microvasculature based on normalized differentiation analysis
Author(s) -
Zhu Jiang,
Liu Jianting,
Zhu Lianqing,
Wang Chongyang,
Fan Fan,
Yang Qiang,
Zhang Fan
Publication year - 2020
Publication title -
journal of biophotonics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 66
eISSN - 1864-0648
pISSN - 1864-063X
DOI - 10.1002/jbio.202000245
Subject(s) - blood flow , imaging phantom , image quality , computation , optical coherence tomography , normalization (sociology) , angiography , tomography , biomedical engineering , cerebral blood flow , automatic differentiation , coherence (philosophical gambling strategy) , computer science , optics , artificial intelligence , mathematics , medicine , radiology , physics , algorithm , image (mathematics) , cardiology , statistics , sociology , anthropology
Abstract Optical coherence tomography angiography (OCTA) is a label‐free, noninvasive biomedical imaging modality for mapping microvascular networks and quantifying blood flow velocities in vivo . Simple computation and fast processing are critical for the OCTA in some applications. Herein, we report on a normalized differentiation method for mapping cerebral microvasculature with the advantages of simple analysis and high image quality, benefitting from computation of differentiation and characteristics of normalization. Normalized differentiation values are validated to have a nearly linear relationship with flow velocities in a range using a flow phantom. The measurements in a rat cerebral cortex show that the OCTA based on the normalized differentiation analysis can generate microvascular images with high quality and monitor spatiotemporal dynamics of blood flow with simple computation and fast processing before and after localized ischemia induced by arterial occlusion.