DocumentCode :
1506172
Title :
Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation
Author :
Zana, Frédéric ; Klein, Jean-Claude
Author_Institution :
Centre de Morphologie Math., Ecole des Mines de Paris, Valbonne, France
Volume :
10
Issue :
7
fYear :
2001
fDate :
7/1/2001 12:00:00 AM
Firstpage :
1010
Lastpage :
1019
Abstract :
This paper presents an algorithm based on mathematical morphology and curvature evaluation for the detection of vessel-like patterns in a noisy environment. Such patterns are very common in medical images. Vessel detection is interesting for the computation of parameters related to blood flow. Its tree-like geometry makes it a usable feature for registration between images that can be of a different nature. In order to define vessel-like patterns, segmentation is performed with respect to a precise model. We define a vessel as a bright pattern, piece-wise connected, and locally linear, mathematical morphology is very well adapted to this description, however other patterns fit such a morphological description. In order to differentiate vessels from analogous background patterns, a cross-curvature evaluation is performed. They are separated out as they have a specific Gaussian-like profile whose curvature varies smoothly along the vessel. The detection algorithm that derives directly from this modeling is based on four steps: (1) noise reduction; (2) linear pattern with Gaussian-like profile improvement; (3) cross-curvature evaluation; (4) linear filtering. We present its theoretical background and illustrate it on real images of various natures, then evaluate its robustness and its accuracy with respect to noise
Keywords :
Gaussian processes; blood vessels; digital filters; edge detection; eye; image segmentation; interference suppression; mathematical morphology; medical image processing; noise; Gaussian-like profile; blood flow; blood vessels; cross-curvature evaluation; curvature evaluation; detection algorithm; linear filtering; linear pattern; mathematical morphology; medical images; noise reduction; noisy environment; registration; tree-like geometry; vessel detection; vessel-like patterns; Biomedical imaging; Blood flow; Detection algorithms; Gaussian processes; Geometry; Image segmentation; Morphology; Noise reduction; Performance evaluation; Working environment noise;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/83.931095
Filename :
931095
Link To Document :
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