Fluorescence and bright-field 3D image fusion based on sinogram unification for optical projection tomography

Xiaoqin Tang, M. V. Hoff, J. Hoogenboom, Yuanhao Guo, Fuyu Cai, G. Lamers, F. Verbeek
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引用次数: 6

Abstract

In order to preserve sufficient fluorescence intensity and improve the quality of fluorescence images in optical projection tomography (OPT) imaging, a feasible acquisition solution is to temporally formalize the fluorescence and bright-field imaging procedure as two consecutive phases. To be specific, fluorescence images are acquired first, in a full axial-view revolution, followed by the bright-field images. Due to the mechanical drift, this approach, however, may suffer from a deviation of center of rotation (COR) for the two imaging phases, resulting in irregular 3D image fusion, with which gene or protein activity may be located inaccurately. In this paper, we address this problem and consider it into a framework based on sinogram unification so as to precisely fuse 3D images from different channels for CORs between channels that are not coincident or if COR is not in the center of sinogram. The former case corresponds to the COR deviation above; while the latter one correlates with COR alignment, without which artefacts will be introduced in the reconstructed results. After sinogram unification, inverse radon transform can be implemented on each channel to reconstruct the 3D image. The fusion results are acquired by mapping the 3D images from different channels into a common space. Experimental results indicate that the proposed framework gains excellent performance in 3D image fusion from different channels. For the COR alignment, a new automated method based on interest point detection and included in sinogram unification, is presented. It outperforms traditional COR alignment approaches in combination of effectiveness and computational complexity.
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基于正弦图统一的光学投影断层成像荧光与亮场三维图像融合
为了在光学投影层析成像(OPT)中保持足够的荧光强度并提高荧光图像的质量,一种可行的采集方案是将荧光和明场成像过程暂时形式化为两个连续的阶段。具体地说,荧光图像是首先获得的,在一个完整的轴向视图的革命,其次是亮场图像。然而,由于机械漂移,这种方法可能存在两个成像阶段的旋转中心(COR)偏差,导致不规则的3D图像融合,从而可能不准确地定位基因或蛋白质的活性。在本文中,我们解决了这一问题,并将其考虑到一个基于sinogram统一的框架中,以便在不重合通道之间或当COR不在sinogram中心时,对不同通道的3D图像进行精确的CORs融合。前一种情况对应于上述COR偏差;而后者与COR对齐相关,如果没有COR对齐,重构结果中将引入伪影。在正弦图统一后,对每个通道进行逆radon变换,重建三维图像。通过将不同通道的三维图像映射到一个公共空间,获得融合结果。实验结果表明,该框架在不同通道的三维图像融合中取得了较好的效果。提出了一种基于兴趣点检测并包含正弦图统一的自动对齐方法。它在有效性和计算复杂度方面优于传统的COR对齐方法。
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