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AUTOMATED CORRECTION OF METAL AFFECTED VOXEL REPRESENTATIONS OF X-RAY DATA USING DEEP LEARNING TECHNIQUES
AUTOMATED CORRECTION OF METAL AFFECTED VOXEL REPRESENTATIONS OF X-RAY DATA USING DEEP LEARNING TECHNIQUES
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机译：运用深度学习技术自动校正金属影响的X射线数据体素表示
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摘要
A computer-implemented method for correction of a voxel representation of metal affected x-ray data is described,themetal affected x-ray data representing artefacts in the x-ray data caused by metal or metallic objects in a volume of tissue that is imaged by an x-ray imager, wherein the method comprises a first 3D deep neural network receiving an initial voxel representation of metal affected x-ray data at its input and generating a voxel map at its output, the voxel map identifying voxels of the initial voxel representation that belong to a region of voxels that are affected by metal; and, a second 3D deep neural network receiving the initial voxel representation and the voxel map generated by the first 3D deep neural network at its input and generating a corrected voxel representation,the corrected voxel representation including voxel estimations for voxels that are identified by the voxel map as being part of a metal affected region, the first 3D deep neural being trained on the basis of training data and reference data that include voxel representations of clinical x- ray data of a predetermined body part of a patient.
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