Segmentation and quantification of the aortic arch using joint 3D model-based segmentation and elastic image registration

Accurate quantification of the morphology of vessels is important for diagnosis and treatment of cardiovascular diseases. We introduce a new joint segmentation and registration approach for the quantification of the aortic arch morphology that combines 3D model-based segmentation with elastic image...

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Main Authors: Biesdorf, Andreas (Author) , Rohr, Karl (Author) , Feng, Duan (Author) , Tengg-Kobligk, Hendrik von (Author) , Rengier, Fabian (Author) , Böckler, Dittmar (Author) , Kauczor, Hans-Ulrich (Author) , Wörz, Stefan (Author)
Format: Article (Journal)
Language:English
Published: 21 June 2012
In: Medical image analysis
Year: 2012, Volume: 16, Issue: 6, Pages: 1187-1201
ISSN:1361-8423
DOI:10.1016/j.media.2012.05.010
Online Access:Verlag, Volltext: http://dx.doi.org/10.1016/j.media.2012.05.010
Verlag, Volltext: http://www.sciencedirect.com/science/article/pii/S1361841512000771
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Author Notes:Andreas Biesdorf, Karl Rohr, Duan Feng, Hendrik von Tengg-Kobligk, Fabian Rengier, Dittmar Böckler, Hans-Ulrich Kauczor, Stefan Wörz
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Summary:Accurate quantification of the morphology of vessels is important for diagnosis and treatment of cardiovascular diseases. We introduce a new joint segmentation and registration approach for the quantification of the aortic arch morphology that combines 3D model-based segmentation with elastic image registration. With this combination, the approach benefits from the robustness of model-based segmentation and the accuracy of elastic registration. The approach can cope with a large spectrum of vessel shapes and particularly with pathological shapes that deviate significantly from the underlying model used for segmentation. The performance of the approach has been evaluated on the basis of 3D synthetic images, 3D phantom data, and clinical 3D CTA images including pathologies. We also performed a quantitative comparison with previous approaches.
Item Description:Available online 21 June 2012
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Physical Description:Online Resource
ISSN:1361-8423
DOI:10.1016/j.media.2012.05.010