Authors:
Eric Brassart
1
;
Cyril Drocourt
1
;
Jacques Rochette
2
;
Michel Slama
3
and
Carole Amant
2
Affiliations:
1
LTI, Univerty of Picardie Jules Verne and IUT Amiens, France
;
2
DMAG; Univerty of Picardie Jules Verne; CHU, France
;
3
INSERM; Univerty of Picardie Jules Verne; CHU, France
Keyword(s):
Angiogenesis, Image analysis, Capillary tube network.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Medical Image Detection, Acquisition, Analysis and Processing
Abstract:
Angiogenesis, the formation of new capillary blood vessels from pre-existing vessel, has become an important area of scientific research. Numerous in vivo and in vitro angiogenesis assays have been developed in order to test molecules designed to cure deregulated angiogenesis. But unlike most animal models, most in vitro angiogenesis models are not yet automatically analysed and conclusion and data quantification depend on the observer’s analysis. In our study, we will develop a new automatic in vitro matrigel angiogenesis analysis allowing tube length and the number of tubes per cell islets as well as cell islet and tubule mapping to be determined, percentage of vascularisation area, the determination of ratio of tubule length per number of cells in cell islet and, ratio length/width per tubule determination. This new method will also take image noise into account. Our method uses classical imaging quantification. For the first image processing we used image segmentation (Sobel type
edge detection) and artefact erasing (morphologic operator). Subsequent image processing used Snakes: Active contour models in order to precisely detect cells or cell islets. We suggest that this new automated image analysis method for quantification of in vitro angiogenesis will give the researcher vascular specific quantified data that will help in the comparison of samples.
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