Abstract
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.
| Original language | English |
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| Title of host publication | Unknown Host Publication |
| Pages | 101-104 |
| Number of pages | 4 |
| DOIs | |
| Publication status | Published (in print/issue) - 2006 |
| Event | Biomedical Imaging: Macro to Nano, 2006. 3rd IEEE International Symposium on - Duration: 1 Jan 2006 → … |
Conference
| Conference | Biomedical Imaging: Macro to Nano, 2006. 3rd IEEE International Symposium on |
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| Period | 1/01/06 → … |
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