Titlebook: Computational Methods and Clinical Applications for Spine Imaging; Third International Tomaž Vrtovec,Jianhua Yao,Shuo Li Conference procee

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书目名称Computational Methods and Clinical Applications for Spine Imaging影响因子(影响力)




书目名称Computational Methods and Clinical Applications for Spine Imaging影响因子(影响力)学科排名




书目名称Computational Methods and Clinical Applications for Spine Imaging网络公开度




书目名称Computational Methods and Clinical Applications for Spine Imaging网络公开度学科排名




书目名称Computational Methods and Clinical Applications for Spine Imaging被引频次




书目名称Computational Methods and Clinical Applications for Spine Imaging被引频次学科排名




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书目名称Computational Methods and Clinical Applications for Spine Imaging年度引用学科排名




书目名称Computational Methods and Clinical Applications for Spine Imaging读者反馈




书目名称Computational Methods and Clinical Applications for Spine Imaging读者反馈学科排名

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Automatic Modic Changes Classification in Spinal MRItions visible as intensity variations in magnetic resonance images (MRI). The system operates on T1 and T2 MRI. We introduce three main novelties: 1. a vertebrae alignment scheme via precise bounding boxes obtained through corner localisation, 2. vertebral endplate classification in three dimensions

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Robust CT to US 3D-3D Registration by Using Principal Component Analysis and Kalman Filteringtrasound (US) and computerised tomography (CT) scans, effectively handling the US limited depth and low signal-to-noise ratio. Previously proposed methods are accurate, but their convergence rate is considerably reduced with initial misalignments of the datasets greater than . or 30 mm. We propose a

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Cortical Bone Thickness Estimation in CT Images: A Model-Based Approach Without Profile Fittingring of therapy effect. In three-dimensional computed tomography (CT) images, typically cortical thickness in proximal femur, lumbar vertebrae, and sometimes in distal forearm is estimated. However, resolution of clinical quantitative CT (QCT) scanners is comparable to the cortical thickness, especi

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Multi-atlas Segmentation with Joint Label Fusion of Osteoporotic Vertebral Compression Fractures on ological traumas and pathologies. Segmentation is especially challenging in the presence of pathology such as vertebral compression fractures. In this paper, we propose a method to produce segmentations for osteoporotic compression fractured vertebrae by applying a multi-atlas joint label fusion tec

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Statistical Shape Model Construction of Lumbar Vertebrae and Intervertebral Discs in Segmentation fo as well as existing pathology, of the lumbar spine. Prior knowledge, such as expected shape and variation within a sample population, can be incorporated through statistical shape models to optimize the image segmentation process. This paper describes a framework for construction of statistical sha

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