期刊
MICROVASCULAR RESEARCH
卷 122, 期 -, 页码 52-59出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.mvr.2018.11.001
关键词
Optical imaging; Speckle; Biomedical image processing; Blood vessels
资金
- University of California at Riverside (UCR), United States, Graduate Division
- National Science Foundation (NSF), United States, CBET Engineering of Biomedical Systems program [1707190]
- NSF EAGER [1547014]
- NSF PIRE [1545852]
- Direct For Mathematical & Physical Scien [1547014] Funding Source: National Science Foundation
- Directorate For Engineering [1707190] Funding Source: National Science Foundation
- Division Of Materials Research [1547014] Funding Source: National Science Foundation
- Div Of Chem, Bioeng, Env, & Transp Sys [1707190] Funding Source: National Science Foundation
- Office Of The Director
- Office Of Internatl Science &Engineering [1545852] Funding Source: National Science Foundation
Since of its introduction in 1980s, laser speckle imaging has become a powerful tool in flow imaging. Its high performance and low cost made it one of the preferable imaging methods. Initially, speckle contrast measurements were the main algorithm for analyzing laser speckle images in biological flows. Speckle contrast measurements, also referred as Laser Speckle Contrast Imaging (LSCI), use statistical properties of speckle patterns to create mapped image of the blood vessels. In this communication, a new method named Laser Speckle Optical Flow Imaging (LSOFI) is introduced. This method uses the optical flow algorithms to calculate the apparent motion of laser speckle patterns. The differences in the apparent motion of speckle patterns are used to identify the blood vessels from surrounding tissue. LSOFI has better spatial and temporal resolution compared to LSCI. This higher spatial resolution enables LSOFI to be used for autonomous blood vessels detection. Furthermore, Graphics Processing Unit (GPU) based LSOFI can be used for quasi real time imaging.
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