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Reconstruction of 3D lumvar vertebra from two X-ray images based on 2D/3D registration

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机构： [1]Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China [2]University of Chinese Academy of Sciences, Beijing, China [3]Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing, China [4]Division of Spine, Department of Neurosurgery, Xuanwu Hospital, China International Neurological Institute, Capital Medical University, Beijing, China [5]Department of Neurosurgery, Beijing Hospital, Beijing, China

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关键词： 2D/2D deformable registration 2D/3D registration 3D reconstruction Lumbar vertebra model X-ray images

摘要：

Constructing a 3D bone from two X-ray images is a challenging task, especially when we would like to build a complicated structure like spine. This paper presents a novel method for reconstructing lumbar vertebra by building correspondence of two X-ray images with a prior model. First, the pose between X-ray images and the vertebra model was estimated; second, the correspondences between the Digitally Reconstructed Radiographies (DRRs) and vertebra model were built; third, the deformation field from DRRs to X-ray images was calculated; last, deformation field was applied to vertebra model to generate the patient’s specified 3D model. This method just needs one prior model for 3D reconstruction. The experiments on nine vertebrae of three patients show the average reconstruction error is 1.2mm (1.0 mm–1.3mm) which is comparable to the state of the art. © Springer International Publishing AG 2016.

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第一作者机构： [1]Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China [2]University of Chinese Academy of Sciences, Beijing, China

通讯作者：

通讯机构： [1]Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China [2]University of Chinese Academy of Sciences, Beijing, China [3]Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing, China

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