Intravital X-ray microscopy (XRM) in preclinical mouse models is of vital importance for the identification of microscopic structural pathological changes in the bone which are characteristic of osteoporosis. The complexity of this method stems from the requirement for high-quality 3D reconstructions of the murine bones. However, respiratory motion and muscle relaxation lead to inconsistencies in the projection data which result in artifacts in uncompensated reconstructions. Motion compensation using epipolar consistency conditions (ECC) has previously shown good performance in clinical CT settings. Here, we explore whether such algorithms are suitable for correcting motion-corrupted XRM data. Different rigid motion patterns are simulated and the quality of the motion-compensated reconstructions is assessed. The method is able to restore microscopic features for out-of-plane motion, but artifacts remain for more realistic motion patterns including all six degrees of freedom of rigid motion. Therefore, ECC is valuable for the initial alignment of the projection data followed by further fine-tuning of motion parameters using a reconstruction-based method

翻译：活体小鼠模型的X射线显微成像对于识别骨质疏松症特征性的骨微观结构病理变化至关重要。该方法的复杂性源于需要获得鼠骨的高质量三维重建图像。然而，呼吸运动与肌肉松弛会导致投影数据不一致，从而在未补偿的重建图像中产生伪影。基于极线一致性条件的运动补偿方法此前已在临床CT场景中展现出良好性能。本研究探讨此类算法是否适用于校正受运动影响的X射线显微成像数据。我们模拟了不同刚体运动模式，并评估了运动补偿重建图像的质量。该方法能够恢复平面外运动引起的微观结构特征，但对于包含刚体运动全部六个自由度的更真实运动模式仍存在伪影。因此，极线一致性条件适用于投影数据的初始配准，后续需结合基于重建的方法对运动参数进行精细调整。