Anatomy Detection and Localization in 3D Medical Images

Author:

Criminisi A.,Robertson D.,Pauly O.,Glocker B.,Konukoglu E.,Shotton J.,Mateus D.,Martinez Möller A.,Nekolla S. G.,Navab N.

Publisher

Springer London

Reference29 articles.

1. Criminisi A, Shotton J, Bucciarelli S (2009) Decision forests with long-range spatial context for organ localization in CT volumes. In: MICCAI workshop on probabilistic models for medical image analysis (PMMIA)

2. Criminisi A, Shotton J, Robertson D, Konukoglu E (2010) Regression forests for efficient anatomy detection and localization in CT studies. In: MICCAI workshop on medical computer vision: recognition techniques and applications in medical imaging, Beijing. Springer, Berlin

3. Criminisi A, Shotton J, Konukoglu E (2012) Decision forests: a unified framework for classification, regression, density estimation, manifold learning and semi-supervised learning. Found Trends Comput Graph Vis 7(2–3)

4. Fenchel M, Thesen S, Schilling A (2008) Automatic labeling of anatomical structures in MR FastView images using a statistical atlas. In: Proc medical image computing and computer assisted intervention (MICCAI)

5. Feulner J, Zhou SK, Seifert S, Cavallaro A, Hornegger J, Comaniciu D (2009) Estimating the body portion of CT volumes by matching histograms of visual words. In: Pluim JPW, Dawant BM (eds) Proc Intl society for optical engineering (SPIE) medical imaging

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