BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

174 related articles for article (PubMed ID: 24184436)

  • 1. A conditional statistical shape model with integrated error estimation of the conditions; application to liver segmentation in non-contrast CT images.
    Tomoshige S; Oost E; Shimizu A; Watanabe H; Nawano S
    Med Image Anal; 2014 Jan; 18(1):130-43. PubMed ID: 24184436
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Semi-automatic liver tumor segmentation with hidden Markov measure field model and non-parametric distribution estimation.
    Häme Y; Pollari M
    Med Image Anal; 2012 Jan; 16(1):140-9. PubMed ID: 21742543
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Joint optimization of segmentation and shape prior from level-set-based statistical shape model, and its application to the automated segmentation of abdominal organs.
    Saito A; Nawano S; Shimizu A
    Med Image Anal; 2016 Feb; 28():46-65. PubMed ID: 26716720
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A likelihood and local constraint level set model for liver tumor segmentation from CT volumes.
    Li C; Wang X; Eberl S; Fulham M; Yin Y; Chen J; Feng DD
    IEEE Trans Biomed Eng; 2013 Oct; 60(10):2967-77. PubMed ID: 23771304
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A generic probabilistic active shape model for organ segmentation.
    Wimmer A; Soza G; Hornegger J
    Med Image Comput Comput Assist Interv; 2009; 12(Pt 2):26-33. PubMed ID: 20426092
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A probabilistic model for automatic segmentation of the esophagus in 3-D CT scans.
    Feulner J; Zhou SK; Hammon M; Seifert S; Huber M; Comaniciu D; Hornegger J; Cavallaro A
    IEEE Trans Med Imaging; 2011 Jun; 30(6):1252-64. PubMed ID: 21303741
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Abdominal multi-organ segmentation from CT images using conditional shape-location and unsupervised intensity priors.
    Okada T; Linguraru MG; Hori M; Summers RM; Tomiyama N; Sato Y
    Med Image Anal; 2015 Dec; 26(1):1-18. PubMed ID: 26277022
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Liver segmentation approach using graph cuts and iteratively estimated shape and intensity constrains.
    Afifi A; Nakaguchi T
    Med Image Comput Comput Assist Interv; 2012; 15(Pt 2):395-403. PubMed ID: 23286073
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A generalized active shape model for segmentation of liver in low-contrast CT volumes.
    Esfandiarkhani M; Foruzan AH
    Comput Biol Med; 2017 Mar; 82():59-70. PubMed ID: 28161593
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Model-based segmentation using graph representations.
    Seghers D; Hermans J; Loeckx D; Maes F; Vandermeulen D; Suetens P
    Med Image Comput Comput Assist Interv; 2008; 11(Pt 1):393-400. PubMed ID: 18979771
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Liver segmentation using automatically defined patient specific B-spline surface models.
    Song Y; Bulpitt AJ; Brodlie KW
    Med Image Comput Comput Assist Interv; 2009; 12(Pt 2):43-50. PubMed ID: 20426094
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automated segmentation of the liver from 3D CT images using probabilistic atlas and multi-level statistical shape model.
    Okada T; Shimada R; Sato Y; Hori M; Yokota K; Nakamoto M; Chen YW; Nakamura H; Tamura S
    Med Image Comput Comput Assist Interv; 2007; 10(Pt 1):86-93. PubMed ID: 18051047
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Atlas-based automated segmentation of spleen and liver using adaptive enhancement estimation.
    Linguraru MG; Sandberg JK; Li Z; Pura JA; Summers RM
    Med Image Comput Comput Assist Interv; 2009; 12(Pt 2):1001-8. PubMed ID: 20426209
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Semi-automatic level set segmentation of liver tumors combining a spiral-scanning technique with supervised fuzzy pixel classification.
    Smeets D; Loeckx D; Stijnen B; De Dobbelaer B; Vandermeulen D; Suetens P
    Med Image Anal; 2010 Feb; 14(1):13-20. PubMed ID: 19828356
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Non-parametric iterative model constraint graph min-cut for automatic kidney segmentation.
    Freiman M; Kronman A; Esses SJ; Joskowicz L; Sosna J
    Med Image Comput Comput Assist Interv; 2010; 13(Pt 3):73-80. PubMed ID: 20879385
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Constructing a probabilistic model for automated liver region segmentation using non-contrast X-ray torso CT images.
    Zhou X; Kitagawa T; Hara T; Fujita H; Zhang X; Yokoyama R; Kondo H; Kanematsu M; Hoshi H
    Med Image Comput Comput Assist Interv; 2006; 9(Pt 2):856-63. PubMed ID: 17354853
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Automatic X-ray landmark detection and shape segmentation via data-driven joint estimation of image displacements.
    Chen C; Xie W; Franke J; Grutzner PA; Nolte LP; Zheng G
    Med Image Anal; 2014 Apr; 18(3):487-99. PubMed ID: 24561486
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Fast automatic segmentation of the esophagus from 3D CT data using a probabilistic model.
    Feulner J; Zhou SK; Cavallaro A; Seifert S; Hornegger J; Comaniciu D
    Med Image Comput Comput Assist Interv; 2009; 12(Pt 1):255-62. PubMed ID: 20425995
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Automated segmentation of the liver from 3D CT images using probabilistic atlas and multilevel statistical shape model.
    Okada T; Shimada R; Hori M; Nakamoto M; Chen YW; Nakamura H; Sato Y
    Acad Radiol; 2008 Nov; 15(11):1390-403. PubMed ID: 18995190
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Quantitative vertebral morphometry using neighbor-conditional shape models.
    de Bruijne M; Lund MT; Tankó LB; Pettersen PC; Nielsen M
    Med Image Anal; 2007 Oct; 11(5):503-12. PubMed ID: 17720611
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.