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References
1. Corso J, Raja
S A, Chaudhary V (2008) Lumbar disc localization and labeling with a
probabilistic model on both pixel and object features. In: MICCAI, pp 202
'
210
2. Schmidt S, Kappes J, Bergtholdt M, Pekar V, Dries S, Bystrov D, Schnoerr C (2007) Spine
detection and labeling using a parts-based graphical model. IPMI 4584(2007):122
-
133
3. Oktay A, Akgul Y (2011) Localization of the lumbar discs using machine learning and exact
probabilistic inference. In: Fichtinger G, Martel A, Peters T (eds) MICCAI. vol 6893 of
LNCS. Springer, Berlin, pp 159 - 165
4. Kappes J (2011) Inference on highly-connected discrete graphical models with applications to
visual object recognition. PhD thesis
5. Glocker B, Feulner J, Criminisi A, Haynor DR, Konukoglu E (2012) automatic localization
and identification of vertebrae in arbitrary field-of-view CT scans. In: 15th international
conference on medical image computing and computer assisted intervention (MICCAI)
6. Klinder T, Ostermann J, Ehm M, Franz A, Kneser R, Lorenz C (2009) Automated model-
based vertebra detection, identification, and segmentation in CT images. Med Image Anal
13:471
-
482
7. Murphy KP, Weiss Y, Jordan MI (1999) Loopy belief propagation for approximate inference:
an empirical study. In: Proceedings of uncertainty in AI, pp 467
-
475
8. Comaniciu D, Meer P (2002) Mean shift: a robust approach toward feature space analysis.
IEEE Trans Pattern Anal Mach Intell 24:603
-
619
9. Rasoulian A, Rohling RN, Abolmaesumi P (2014) Automatic labeling and segmentation of
vertebrae in CT images. In: Medical imaging 2014: image-guided procedures, robotic
interventions, and modeling, San Diego, California, USA,15 Feb 2014
10. Aslan et al (2011) A new shape based segmentation framework using statistical and variational
methods. In: Proceedings of 2011 IEEE international conference on image processing (ICIP),
pp 717 - 720
-
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