In this paper a novel model driven segmentation approach for thoracic MR-images is presented. The goal of this work is to coarsely, but fully automatically localize the boundary surfaces of the heart and lungs in thoracic MR sets. The major organs in the thorax are described in a three-dimensional analytical model template by combining a set of fuzzy implicit surfaces by means of Constructive Solid Geometry, and formulating model registration as an energy minimization. The method has been validated on 20 thoracic MR volumes from two centers (patients and normal subjects). On average 90% of the contour length of the heart and lung contours was localized with sufficient accuracy (average 6 mm positional error) to automatically provide the initial conditions for a subsequently applied locally accurate segmentation method.
CITATION STYLE
Lelieveldt, B. P. F., Sonka, M., Bolinger, L., Scholz, T. D., Kayser, H. W. M., van Der Geest, R. J., & Reiber, J. H. C. (1999). Anatomical modeling with fuzzy implicit surfaces: Application to automated localization of the heart and lungs in thoracic MR images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1613, pp. 400–405). Springer Verlag. https://doi.org/10.1007/3-540-48714-x_36
Mendeley helps you to discover research relevant for your work.