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Spectral-based 2D/3D X-ray to CT image rigid registration

机译:基于光谱的2D / 3D X射线到CT图像的刚性配准

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We present a spectral-based method for the 2D/3D rigid registration of X-ray images to a CT scan. The method uses a Fourier-based representation to decompose the six rigid transformation parameters problem into a two-parameter out-of-plane rotation and a four-parameter in-plane transformation problems. Preoperatively, a set of Digitally Reconstructed Radiographs (DRRs) are generated offline from the CT in the expected in-plane location ranges of the fluoroscopic X-ray imaging devices. Each DRR is transformed into a imaging device in-plane invariant features space. Intraoperatively, a few 2D projections of the patient anatomy are acquired with an X-ray imaging device. Each projection is transformed into its in-plane invariant representation. The out-of-plane parameters are first computed by maximization of the Normalized Cross-Correlation between the invariant representations of the DRRs and the X-ray images. Then, the in-plane parameters are computed with the phase correlation method based on the Fourier-Mellin transform. Experimental results on publicly available data sets show that our method can robustly estimate the out-of-plane parameters with accuracy of 1.5° in less than lsec for out-of-plane rotations of 10° or more, and perform the entire registration in less than l0secs.
机译:我们提出了一种基于光谱的X射线图像到CT扫描的2D / 3D刚性配准的方法。该方法使用基于傅立叶的表示法将六个刚性变换参数问题分解为两参数平面外旋转问题和四参数平面内变换问题。术前,在透视X射线成像设备的预期面内位置范围内,从CT脱机生成了一组数字重建X射线照片(DRR)。每个DRR都转换为成像设备平面内不变特征空间。术中,使用X射线成像设备获取患者解剖结构的一些2D投影。每个投影都转换为其平面内不变表示。首先通过最大化DRR和X射线图像的不变表示之间的归一化互相关来计算平面外参数。然后,使用基于傅立叶-梅林变换的相位相关方法来计算平面内参数。公开数据集上的实验结果表明,对于面外旋转10°或以上的情况,我们的方法可以在不到1秒的时间内以1.5°的精度可靠地估算面外参数,并在不到100秒的时间内完成整个配准超过10秒。

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