Fully Automated Segmentation of the Psoas Major Muscle in Clinical CT Scans
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Publisher
Springer Fachmedien Wiesbaden
Link
http://link.springer.com/content/pdf/10.1007/978-3-658-29267-6_12
Reference10 articles.
1. Kamiya N, Zhou X, Chen H, et al. Automated segmentation of psoas major muscle in x-ray CT images by use of a shape model: preliminary study. Radiological physics and technology. 2012;5(1):5–14.
2. Inoue T, Kitamura Y, Li Y, et al. Psoas major muscle segmentation using higher-order shape prior. In: International MICCAI Workshop on Medical Computer Vision. Springer; 2015. p. 116–124.
3. Hu P, Huo Y, Kong D, et al. Automated characterization of body composition and frailty with clinically acquired CT. In: International Workshop and Challenge on Computational Methods and Clinical Applications in Musculoskeletal Imaging. Springer; 2017. p. 25–35.
4. Heinrich MP, Blendowski M. Multi-organ segmentation using vantage point forests and binary context features. In: International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer; 2016. p. 598–606.
5. Meesters S, Yokota F, Okada T, et al. Multi atlas-based muscle segmentation in abdominal CT images with varying field of view; 2012. .
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