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Titlebook: Recent Advances in Computational Methods and Clinical Applications for Spine Imaging; Jianhua Yao,Ben Glocker,Shuo Li Book 2015 Springer I

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Localisation of Vertebrae on DXA Images Using Constrained Local Models with Random Forest Regressionained Local Models (RFRV-CLMs) for this task and show that, while they lead to slightly poorer median errors than AAMs, they are much more robust, reducing the proportion of fit failures by 68 %. They are thus more suitable for use in computer-aided VFA systems.
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Bone Profiles: Simple, Fast, and Reliable Spine Localization in CT Scans1.5 and 0.4 s are reported on a single core. Due to its slice-wise nature, the method can be easily parallelized and fractions of the reported runtimes can be further achieved. Our memory requirements are upper bounded by a single CT slice.
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Automated Radiological Grading of Spinal MRI a heterogeneous clinical dataset containing 1,710 Pfirrmann-graded discs, from 285 symptomatic back pain patients. We are able to predict the grade to . precision at 85.8 % accuracy. Our novel method proposes new image features that outperform previous features and utilizes techniques to improve robustness to MR imaging variations.
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