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Proceedings Paper

Model guided diffeomorphic demons for atlas based segmentation
Author(s): K. D. Fritscher; B. Schuler; T. Roth; Ch. Kammerlander; M. Blauth; R. Schubert
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Paper Abstract

Using an atlas, an image can be segmented by mapping its coordinate space to that of the atlas in an anatomically correct way. In order to find the correct mapping between the two different coordinate spaces e.g. diffeomorphic demons registration can be applied. The demons algorithm is a popular choice for deformable image registration and offers the possibility to perform computationally efficient non-rigid (diffeomorphic) registration. However, this registration method is prone to image artifacts and image noise. Therefore it has been the main objective of the presented work to combine the efficiency of diffeomorphic demons and the stability of statistical models. In the presented approach a statistical deformation model that describes "anatomically correct" displacements vector fields for a specific registration problem is used to guide the demons registration algorithm. By projecting the current displacement vector field, which is calculated during any iteration of the registration process, into the model space a regularized version of the vector field can be computed. Using this regularized vector field for the update of the deformation field in the subsequent iteration of the registration process the demons registration algorithm can be guided by the deformation model. The proposed method was evaluated on 21 CT datasets of the right hip. Measuring the average and maximum segmentation error for all 21 datasets and all 120 test configurations it could be demonstrated that the newly proposed algorithm leads to a reduction of the segmentation error of up to 13% compared to using the conventional diffeomorphic demons algorithm.

Paper Details

Date Published: 12 March 2010
PDF: 8 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 762306 (12 March 2010); doi: 10.1117/12.844134
Show Author Affiliations
K. D. Fritscher, Univ. of Health Sciences, Medical Informatics and Technology (Austria)
B. Schuler, Univ. of Health Sciences, Medical Informatics and Technology (Austria)
T. Roth, Medical Univ. Innsbruck (Austria)
Ch. Kammerlander, Medical Univ. Innsbruck (Austria)
M. Blauth, Medical Univ. Innsbruck (Austria)
R. Schubert, Univ. of Health Sciences, Medical Informatics and Technology (Austria)

Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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