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Multiscale edge detection and parametric shape modeling for boundary delineation in optoacoustic images.
In: (37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015, 25-29 August 2015, Milan, Italy). Institute of Electrical and Electronics Engineers (IEEE), 2015. 707-710 (Conf. Proc. IEEE Eng. Med. Biol. Soc.)
In this article, we present a novel scheme for segmenting the image boundary (with the background) in optoacoustic small animal in vivo imaging systems. The method utilizes a multiscale edge detection algorithm to generate a binary edge map. A scale dependent morphological operation is employed to clean spurious edges. Thereafter, an ellipse is fitted to the edge map through constrained parametric transformations and iterative goodness of fit calculations. The method delimits the tissue edges through the curve fitting model, which has shown high levels of accuracy. Thus, this method enables segmentation of optoacoutic images with minimal human intervention, by eliminating need of scale selection for multiscale processing and seed point determination for contour mapping.
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Publication type
Article: Conference contribution
Keywords
Curve Fitting ; Image Edge Detection ; Image Segmentation ; Photoacoustic Effects
Language
english
Publication Year
2015
HGF-reported in Year
0
ISSN (print) / ISBN
1557-170X
ISBN
978-142449271-8
Conference Title
37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Conference Date
25-29 August 2015
Conference Location
Milan, Italy
Quellenangaben
Pages: 707-710
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Reviewing status
Peer reviewed
Institute(s)
Institute of Biological and Medical Imaging (IBMI)
POF-Topic(s)
30205 - Bioengineering and Digital Health
Research field(s)
Enabling and Novel Technologies
PSP Element(s)
G-505590-001
Scopus ID
84953338184
Erfassungsdatum
2016-01-14