Three-dimensional (3D) reconstructions of the human anatomy have been available for surgery planning or diagnostic purposes for a few years now. The different image modalities usually rely on several consecutive two-dimensional (2D) acquisitions in order to reconstruct the 3D volume. Hence, such acquisitions are expensive, time-demanding and often expose the patient to an undesirable amount of radiation. For such reasons, along the most recent years, several studies have been proposed that extrapolate 3D anatomical features from merely 2D exams such as x rays for implant templating in total knee or hip arthroplasties.

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二维数字重建X射线照片的三维图像体积：下肢CT扫描中的深度学习方法

人体解剖学的三维（3D）重建已可用于外科手术计划或诊断目的，已有数年的历史了。不同的图像模态通常依赖于几个连续的二维（2D）采集，以重建3D体积。因此，这样的获取是昂贵的，费时的并且经常使患者暴露于不希望的辐射量。由于这些原因，在最近几年中，已经提出了几项研究，这些研究仅从诸如X射线的2D检查中推断出3D解剖特征，以用于在全膝或髋关节置换术中植入模板。