Segmentation of Neck Lymph Nodes in CT Datasets with Stable 3D Mass-Spring Models

Abstract. The quantitative assessment of neck lymph nodes in the context of malign tumors requires an ecient segmentation technique for lymph nodes in tomographic 3D datasets. We present a Stable 3D MassSpring Model for lymph node segmentation in CT datasets. Our model for the rst time represents concurrently the characteristic gray value range, directed contour information as well as shape knowledge, which leads to a much more robust and ecient segmentation process. Our model design and segmentation accuracy are both evaluated with lymph nodes from clinical CT neck datasets. 1 Motivation The assessment of lymph nodes plays an important role in the diagnosis, staging, treatment and therapy control of malign tumors and their metastases. MRI and CT scans of the respective regions allow for a 3D assessment of the pathological situation, however, an exact quantitative analysis demands an ecient segmentation of the lymph nodes in the 3D datasets. Lymph node segmentation currently has to be ...

• Type: Conference
• Year: 2006
• Where: MICCAI
• Authors: Bernhard Preim, Gero Strauß, Heiko Seim, Ilka Hertel, Jana Dornheim
• Keywords: Lymph Node Segmentation, Medical Imaging, Metastatic Lymph Nodes, MICCAI 2006, Neck Lymph Nodes