Abstract
The preoperative planning of primary tumor resections in the larynx region shall be supported by a 3D visualization of the patient-specific anatomy and pathological situation. This requires a segmentation of the larynx cartilage structures from computed tomography (CT) datasets.
In our work, we use 3D Stable Mass-Spring Models (SMSMs) for this segmentation task. Thereto, we create a specific 3D deformable shape model for the segmentation of the thyroid cartilage. A new concept for elastic initialization of this model is presented, allowing the deformable model to adapt specifically to patient-specific shape variations and pathological deformations.
We show that using our generation and initialization method, prototypical 3D deformable shape models can be adapted to very different patients without any prior training and prior knowledge about new patients’ data.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Myers, E.N. (ed.): Operative Otolaryngology: Head and Neck Surgery, vol. 1, pp. 403–443. W. B. Saunders Company, Philadelphia (1997)
McInerney, T., Terzopoulos, D.: Deformable models in medical image analysis: A survey. Medical Image Analysis 1, 91–108 (1996)
Cohen, I., Cohen, L.D., Ayache, N.: Using deformable surfaces to segment 3d images and infer differential structures. CVGIP: Image Understanding 56, 242–263 (1992)
Bardinet, E., Cohen, L.D., Ayache, N.: A parametric deformable model to fit unstructured 3D data. CVIU 71, 39–54 (1998)
Cootes, T., Edwards, G., Taylor, C.: Comparing active shape models with active appearance models. In: BMVC, pp. 173–182 (1999)
Dornheim, L., Tönnies, K.D., Dornheim, J.: Stable dynamic 3D shape models. In: ICIP, pp. III–1276–III–1279 (2005)
Dornheim, L., Tönnies, K.D., Dixon, K.: Automatic segmentation of the left ventricle in 3D SPECT data by registration with a dynamic anatomic model. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3749, pp. 335–342. Springer, Heidelberg (2005)
Dornheim, L., Dornheim, J., Tönnies, K.D.: Automatic generation of dynamic 3D models for medical segmentation tasks. In: SPIE: Medical Imaging (2006)
Garland, M., Heckbert, P.S.: Surface simplification using quadric error metrics. In: SIGGRAPH, pp. 209–216 (1997)
Dornheim, L., Dornheim, J., Seim, H., Tönnies, K.D.: Aktive Sensoren: Kontextbasierte Filterung von Merkmalen zur modellbasierten Segmentierung. In: Bildverarbeitung für die Medizin (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dornheim, J., Dornheim, L., Preim, B., Hertel, I., Strauss, G. (2006). Generation and Initialization of Stable 3D Mass-Spring Models for the Segmentation of the Thyroid Cartilage. In: Franke, K., Müller, KR., Nickolay, B., Schäfer, R. (eds) Pattern Recognition. DAGM 2006. Lecture Notes in Computer Science, vol 4174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11861898_17
Download citation
DOI: https://doi.org/10.1007/11861898_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44412-1
Online ISBN: 978-3-540-44414-5
eBook Packages: Computer ScienceComputer Science (R0)