Matula P, Kozubek M, Staier F, Hausmann M
Faculty of Informatics, Masaryk University, Botanická 68a, Brno, CZ-602 00, Czech Republic.
J Microsc. 2003 Feb;209(Pt 2):126-42. doi: 10.1046/j.1365-2818.2003.01104.x.
Micro (micro-) axial tomography is a challenging technique in microscopy which improves quantitative imaging especially in cytogenetic applications by means of defined sample rotation under the microscope objective. The advantage of micro-axial tomography is an effective improvement of the precision of distance measurements between point-like objects. Under certain circumstances, the effective (3D) resolution can be improved by optimized acquisition depending on subsequent, multi-perspective image recording of the same objects followed by reconstruction methods. This requires, however, a very precise alignment of the tilted views. We present a novel feature-based image alignment method with a precision better than the full width at half maximum of the point spread function. The features are the positions (centres of gravity) of all fluorescent objects observed in the images (e.g. cell nuclei, fluorescent signals inside cell nuclei, fluorescent beads, etc.). Thus, real alignment precision depends on the localization precision of these objects. The method automatically determines the corresponding objects in subsequently tilted perspectives using a weighted bipartite graph. The optimum transformation function is computed in a least squares manner based on the coordinates of the centres of gravity of the matched objects. The theoretically feasible precision of the method was calculated using computer-generated data and confirmed by tests on real image series obtained from data sets of 200 nm fluorescent nano-particles. The advantages of the proposed algorithm are its speed and accuracy, which means that if enough objects are included, the real alignment precision is better than the axial localization precision of a single object. The alignment precision can be assessed directly from the algorithm's output. Thus, the method can be applied not only for image alignment and object matching in tilted view series in order to reconstruct (3D) images, but also to validate the experimental performance (e.g. mechanical precision of the tilting). In practice, the key application of the method is an improvement of the effective spatial (3D) resolution, because the well-known spatial anisotropy in light microscopy can be overcome. This allows more precise distance measurements between point-like objects.
微（微-）轴断层扫描是显微镜技术中的一项具有挑战性的技术，它通过在显微镜物镜下进行特定的样品旋转，尤其在细胞遗传学应用中改善了定量成像。微轴断层扫描的优势在于有效提高了点状物体之间距离测量的精度。在某些情况下，根据对同一物体的后续多角度图像记录及重建方法，通过优化采集可以提高有效（3D）分辨率。然而，这需要倾斜视图的非常精确的对齐。我们提出了一种基于特征的新型图像对齐方法，其精度优于点扩散函数的半高全宽。这些特征是图像中观察到的所有荧光物体的位置（重心）（例如细胞核、细胞核内的荧光信号、荧光珠等）。因此，实际的对齐精度取决于这些物体的定位精度。该方法使用加权二分图自动在后续倾斜视角中确定相应的物体。基于匹配物体重心的坐标，以最小二乘法计算最佳变换函数。使用计算机生成的数据计算了该方法理论上可行的精度，并通过对从200nm荧光纳米颗粒数据集中获得的真实图像序列进行测试得到了证实。所提出算法的优点是其速度和准确性，这意味着如果包含足够多的物体，实际对齐精度优于单个物体的轴向定位精度。对齐精度可以直接从算法输出中评估。因此，该方法不仅可以应用于倾斜视图系列中的图像对齐和物体匹配以重建（3D）图像，还可以用于验证实验性能（例如倾斜的机械精度）。在实际应用中，该方法的关键应用是提高有效空间（3D）分辨率，因为可以克服光学显微镜中众所周知的空间各向异性。这使得点状物体之间的距离测量更加精确。
