Filtering, fusion, detection and segmentation of microvasculature vessel fluorescence imagery
 
 
Description:  Automatic segmentation of three-dimensional microvascular structures is needed for quantifying morphological changes and remodeling of blood vessels during development, disease and treatment processes. We use an approach for vessel segmentation that combines multiple single focus images use image fusion with robust adaptive and anisotropic filtering. This enables handling varying contrast levels due to diffusivity of the lectin stain, leakage out of vessels and detecting fine morphological vessel structure. Thresholding and active contour segmentation methods are investigated to extract the vasculature structures. Quantitative parameters of the microvascular network geometry, including curvature, tortuosity, branch segments and branch angles are computed using post segmentation-based medial axis tracing. Experiments using epifluorescence images of mice dura mater demonstrates the effectiveness of the proposed approach for quantifying morphological properties of vascular networks.
Date:  2015-07-07
Start Time:   11:00
Speaker:  Kannappan Palaniappan (Univ. Missouri, Columbia, USA)
Institution:  Univ. Missouri, Columbia, USA
Place:  Room 5.5
Research Groups: -Analysis
-Numerical Analysis and Optimization
See more:   <Main>  
 
Attached Files
 
File Description
Short Bio
One register found.1
© Centre for Mathematics, University of Coimbra, funded by
Science and Technology Foundation
Powered by: rdOnWeb v1.4 | technical support