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

Academic Radiology

Volumn 14, Issue 11, 2007, Pages 1389-1399

  Dornheim, Jana ^a   Seim, Heiko ^b   Preim, Bernhard ^a   Hertel, Ilka ^c   Strauss, Gero ^c  

^a OTTO VON GUERICKE UNIVERSITY   (Germany)

^b ZUSE INSTITUTE BERLIN   (Germany)

^c UNIVERSITY HOSPITAL LEIPZIG   (Germany)

Author keywords

CT; deformable models; lymph nodes; Segmentation; stable mass spring models

Indexed keywords

ARTICLE; CERVICAL LYMPH NODE; COMPUTER ASSISTED TOMOGRAPHY; DIAGNOSTIC ACCURACY; HUMAN; NECK TUMOR; PRIORITY JOURNAL; SIMULATION; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DATABASES, FACTUAL; ELASTICITY; HEAD AND NECK NEOPLASMS; HUMANS; IMAGING, THREE-DIMENSIONAL; LYMPH NODES; LYMPHATIC METASTASIS; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; STRESS, MECHANICAL; TOMOGRAPHY, X-RAY COMPUTED;

EID: 35348967271     PISSN: 10766332     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.acra.2007.09.001     Document Type: Article

References (12)

1. Cordes J., Dornheim J., Preim B., et al. Strauss: Preoperative segmentation of neck CT datasets for the planning of neck dissections. Proc SPIE Med Imaging 2006: Image Processing (2006)
2. Rogowska J., Batchelder K., Gazelle G., et al. Evaluation of selected two-dimensional segmentation techniques for computed tomography quantification of lymph nodes. Investig Radiol 13 (1996) 138-145
3. Honea D.M., Ge Y., Snyder W.E., et al. Lymph node segmentation using active contours. Proc SPIE Med Imaging 1997: Image Processing 3034 (1997) 265-273
4. Honea D., and Snyder W.E. Three-dimensional active surface approach to lymph node segmentation. Proc SPIE Med Imaging 1999: Image Processing 3361 (1999) 1003-1011
5. Yan J., Zhuang T., Zhao B., et al. Lymph node segmentation from CT images using fast marching method. Comp Med Imaging Graphics 28 (2004) 33-38
6. Kuhnigk J.-M., Dicken V., Bornemann L., et al. Fast automated segmentation and reproducible volumetry of pulmonary metastases in CT-scans for therapy monitoring. MICCAI (2004) 933-941
7. Dornheim L., Tönnies K.D., and Dornheim J. Stable dynamic 3D shape models. Int Conf Image Proc (ICIP) (2005)
8. Dornheim L., Dornheim J., and Tönnies K.D. Automatic generation of dynamic 3D models for medical segmentation tasks. SPIE Med Imaging (2006)
9. Unal G., Slabaugh G., Ess A., et al. Semi-automatic lymph node segmentation in LN-MRI. Int Conf Image Proc (ICIP) (2006)
10. Cohen I., Cohen L.D., and Ayache N. Using deformable surfaces to segment 3d images and infer differential structures. CVGIP: Image Understanding 56 2 (1992) 242-263
11. Delingette H. Adaptive and deformable models based on Simplex Meshes. IEEE Workshop of Non-Rigid and Articulated Objects (1994)
12. Montagnat J., and Delingette H. Volumetric medical images segmentation using shape-constrained deformable models. CVRMed (1997) 13-22