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UNCERTAINTY MAPS FOR SEGMENTATION IN THE PRESENCE OF METAL ARTIFACTS

机译:存在金属制品时进行分段的不确定性图

摘要

When performing model-based segmentation on a 3D patient image (80), metal artifacts in the patient image (80), caused by metal in the patient's body, are detected, and a metal artifact reduction technique is performed to reduce the artifact(s) by interpolation projection data in the region of the artifact(s). The interpolated data is used to generate an uncertainty map for artifact-affected voxels in the image, and a mesh model (78) is conformed to the image to facilitate segmentation thereof. Internal and external energies applied to push and pull the model (78) are weighted as a function of the uncertainty associated with one or more voxels in the image (80). Iteratively, mathematical representations of the energies and respective weights are solved to describe an updated model shape that more closely aligns to the image (80).
机译:当对3D患者图像(80)执行基于模型的分割时,检测由患者体内金属引起的患者图像(80)中的金属伪影,并执行金属伪影减少技术以减少伪影)通过在伪影区域内插入投影数据进行插值。内插的数据用于生成图像中受伪影影响的体素的不确定性图,并且网格模型(78)符合图像以利于其分割。根据与图像(80)中的一个或多个体素相关的不确定性来加权施加于推拉模型(78)的内部和外部能量。迭代地,求解能量和各个权重的数学表示,以描述更紧密地与图像对齐的更新的模型形状(80)。

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