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Application of optical flow algorithms to laser speckle imaging.
Aminfar, AmirHessam; Davoodzadeh, Nami; Aguilar, Guillermo; Princevac, Marko.
Afiliação
  • Aminfar A; Department of Mechanical Engineering, University of California Riverside, Riverside, CA 92521, United States of America. Electronic address: aamin006@ucr.edu.
  • Davoodzadeh N; Department of Mechanical Engineering, University of California Riverside, Riverside, CA 92521, United States of America.
  • Aguilar G; Department of Mechanical Engineering, University of California Riverside, Riverside, CA 92521, United States of America.
  • Princevac M; Department of Mechanical Engineering, University of California Riverside, Riverside, CA 92521, United States of America.
Microvasc Res ; 122: 52-59, 2019 03.
Article em En | MEDLINE | ID: mdl-30414869
ABSTRACT
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Crânio / Algoritmos / Interpretação de Imagem Assistida por Computador / Fluxometria por Laser-Doppler / Imagem Óptica Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Microvasc Res Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Crânio / Algoritmos / Interpretação de Imagem Assistida por Computador / Fluxometria por Laser-Doppler / Imagem Óptica Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Microvasc Res Ano de publicação: 2019 Tipo de documento: Article