172 related articles for article (PubMed ID: 20879211)
1. Automatic detection and segmentation of axillary lymph nodes.
Barbu A; Suehling M; Xu X; Liu D; Zhou SK; Comaniciu D
Med Image Comput Comput Assist Interv; 2010; 13(Pt 1):28-36. PubMed ID: 20879211
[TBL] [Abstract][Full Text] [Related]
2. Automatic detection and segmentation of lymph nodes from CT data.
Barbu A; Suehling M; Xu X; Liu D; Zhou SK; Comaniciu D
IEEE Trans Med Imaging; 2012 Feb; 31(2):240-50. PubMed ID: 21968722
[TBL] [Abstract][Full Text] [Related]
3. Lymph node detection and segmentation in chest CT data using discriminative learning and a spatial prior.
Feulner J; Zhou SK; Hammon M; Hornegger J; Comaniciu D
Med Image Anal; 2013 Feb; 17(2):254-70. PubMed ID: 23246185
[TBL] [Abstract][Full Text] [Related]
4. Segmentation of neck lymph nodes in CT datasets with stable 3D mass-spring models.
Dornheim J; Seim H; Preim B; Hertel I; Strauss G
Med Image Comput Comput Assist Interv; 2006; 9(Pt 2):904-11. PubMed ID: 17354859
[TBL] [Abstract][Full Text] [Related]
5. Segmentation of neck lymph nodes in CT datasets with stable 3D mass-spring models segmentation of neck lymph nodes.
Dornheim J; Seim H; Preim B; Hertel I; Strauss G
Acad Radiol; 2007 Nov; 14(11):1389-99. PubMed ID: 17964462
[TBL] [Abstract][Full Text] [Related]
6. Automated extraction of lymph nodes from 3-D abdominal CT images using 3-D minimum directional difference filter.
Kitasaka T; Tsujimura Y; Nakamura Y; Mori K; Suenaga Y; Ito M; Nawano S
Med Image Comput Comput Assist Interv; 2007; 10(Pt 2):336-43. PubMed ID: 18044586
[TBL] [Abstract][Full Text] [Related]
7. Mediastinal atlas creation from 3-D chest computed tomography images: application to automated detection and station mapping of lymph nodes.
Feuerstein M; Glocker B; Kitasaka T; Nakamura Y; Iwano S; Mori K
Med Image Anal; 2012 Jan; 16(1):63-74. PubMed ID: 21641269
[TBL] [Abstract][Full Text] [Related]
8. Precise segmentation of multiple organs in CT volumes using learning-based approach and information theory.
Lu C; Zheng Y; Birkbeck N; Zhang J; Kohlberger T; Tietjen C; Boettger T; Duncan JS; Zhou SK
Med Image Comput Comput Assist Interv; 2012; 15(Pt 2):462-9. PubMed ID: 23286081
[TBL] [Abstract][Full Text] [Related]
9. The feasibility of hybrid automatic segmentation of axillary lymph nodes from a 3-D sonogram.
Sammet S; Evans KD; Irfanoglu MO; Strapp A; Machiraju R
Ultrasound Med Biol; 2011 Dec; 37(12):2075-85. PubMed ID: 22033128
[TBL] [Abstract][Full Text] [Related]
10. Semiautomatic lymph node segmentation in multislice computed tomography: impact of slice thickness on segmentation quality, measurement precision, and interobserver variability.
Buerke B; Puesken M; Beyer F; Gerss J; Weckesser M; Seifarth H; Heindel W; Wessling J
Invest Radiol; 2010 Feb; 45(2):82-8. PubMed ID: 20027120
[TBL] [Abstract][Full Text] [Related]
11. Coronary lumen segmentation using graph cuts and robust kernel regression.
Schaap M; Neefjes L; Metz C; van der Giessen A; Weustink A; Mollet N; Wentzel J; van Walsum TW; Niessen W
Inf Process Med Imaging; 2009; 21():528-39. PubMed ID: 19694291
[TBL] [Abstract][Full Text] [Related]
12. MSCT follow-up in malignant lymphoma: comparison of manual linear measurements with semi-automated lymph node analysis for therapy response classification.
Weßling J; Puesken M; Koch R; Kohlhase N; Persigehl T; Mesters R; Heindel W; Buerke B
Rofo; 2012 Sep; 184(9):795-804. PubMed ID: 22618478
[TBL] [Abstract][Full Text] [Related]
13. 2D view aggregation for lymph node detection using a shallow hierarchy of linear classifiers.
Seff A; Lu L; Cherry KM; Roth HR; Liu J; Wang S; Hoffman J; Turkbey EB; Summers RM
Med Image Comput Comput Assist Interv; 2014; 17(Pt 1):544-52. PubMed ID: 25333161
[TBL] [Abstract][Full Text] [Related]
14. Fast and robust clinical triple-region image segmentation using one level set function.
Li S; Fevens T; Krzyzak A; Jin C; Li S
Med Image Comput Comput Assist Interv; 2006; 9(Pt 2):766-73. PubMed ID: 17354842
[TBL] [Abstract][Full Text] [Related]
15. Weights and topology: a study of the effects of graph construction on 3D image segmentation.
Grady L; Jolly MP
Med Image Comput Comput Assist Interv; 2008; 11(Pt 1):153-61. PubMed ID: 18979743
[TBL] [Abstract][Full Text] [Related]
16. Automated model-based rib cage segmentation and labeling in CT images.
Klinder T; Lorenz C; von Berg J; Dries SP; Bülow T; Ostermann J
Med Image Comput Comput Assist Interv; 2007; 10(Pt 2):195-202. PubMed ID: 18044569
[TBL] [Abstract][Full Text] [Related]
17. Localized priors for the precise segmentation of individual vertebras from CT volume data.
Shen H; Litvin A; Alvino C
Med Image Comput Comput Assist Interv; 2008; 11(Pt 1):367-75. PubMed ID: 18979768
[TBL] [Abstract][Full Text] [Related]
18. Medical image analysis of 3D CT images based on extension of Haralick texture features.
Tesar L; Shimizu A; Smutek D; Kobatake H; Nawano S
Comput Med Imaging Graph; 2008 Sep; 32(6):513-20. PubMed ID: 18614335
[TBL] [Abstract][Full Text] [Related]
19. Improve threshold segmentation using features extraction to automatic lung delimitation.
França C; Vasconcelos G; Diniz P; Melo P; Diniz J; Novaes M
Stud Health Technol Inform; 2013; 192():1159. PubMed ID: 23920933
[TBL] [Abstract][Full Text] [Related]
20. Segmentation of thin structures in volumetric medical images.
Holtzman-Gazit M; Kimmel R; Peled N; Goldsher D
IEEE Trans Image Process; 2006 Feb; 15(2):354-63. PubMed ID: 16479805
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
