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:在临床前的老鼠模型中,外向X射线显微镜(XRM)对于确定骨骼中具有骨质疏松特征的微生物结构病理变化至关重要。这种方法的复杂性来自对骨质骨骼进行高质量的三维重建的要求。然而,呼吸运动和肌肉放松导致预测数据不一致,导致在未经补偿的重建过程中出现人工制品。使用上皮相一致性条件(ECC)进行运动补偿以前在临床CT环境中表现良好。在这里,我们探讨这些算法是否适合纠正运动干扰的XRM数据。模拟了不同的僵硬运动模式,并评估了运动调整后重建的质量。这种方法能够恢复出板运动的微镜特征,但人工制品仍然用于更现实的动作模式,包括所有六度的僵硬运动自由。因此,ECC对于预测数据的初步调整很有价值,随后采用基于重建的方法进一步调整运动参数。因此,ECC对预测数据的初步调整很有价值。</s>