Ulster University Logo

A fast, robust and scale-independent approach to estimate vessel diameters in intravital fluorescence microscopy images

McEnery, O., Lucas, L., Ma, YingLiang, Morrow, PJ, Mitchell, Christopher and Saetzler, Kurt (2006) A fast, robust and scale-independent approach to estimate vessel diameters in intravital fluorescence microscopy images. In: Biomedical Imaging: Macro to Nano, 2006. 3rd IEEE International Symposium on. UNSPECIFIED. 4 pp. [Conference contribution]

Full text not available from this repository.

DOI: 10.1109/ISBI.2006.1624862


Analyzing dynamic biological systems, such as blood vessel growth in healing wounds or tumour development, requires high spatial and temporal resolution. Intravital fluorescence microscopy allows for longitudinal subcellular imaging, but it requires the use of advanced image analysis tools in order to quantitatively extract the relevant parameters or the topology of the underlying network structure to subsequently model and simulate such a system mathematically. We will present a fast and robust approach that estimates the vessel diameter with a low coefficient of error < 6% in settings that are typical for such in-vivo imaging scenarios with a low signal-to-noise ratio and often sub-optimal and uneven background illumination. The generated vessel network is geometrically cleansed for an optimal topological representation.

Item Type:Conference contribution (Poster)
Keywords:biomedical optical imaging, blood vessels, fluorescence, image representation, medical image processing, optical microscopy, advanced image analysis tools, blood vessel growth, dynamic biological systems, healing wounds, high spatial resolution, high temporal resolution, in-vivo imaging, intravital fluorescence microscopy images, longitudinal subcellular imaging, low signal-to-noise ratio, optimal topological representation, suboptimal background illumination, tumour development, uneven background illumination, vessel diameter estimation
Faculties and Schools:Faculty of Life and Health Sciences
Faculty of Life and Health Sciences > School of Biomedical Sciences
Research Institutes and Groups:Biomedical Sciences Research Institute
Computer Science Research Institute
Biomedical Sciences Research Institute > Genomic Medicine
ID Code:3774
Deposited By: Dr Kurt Saetzler
Deposited On:01 Feb 2010 10:20
Last Modified:10 May 2017 10:49

Repository Staff Only: item control page