COMPUTATIONAL OPTICAL SECTIONING MICROSCOPY ALGORITHMS

三维(3D)荧光显微镜是一种强大的工具 对活体标本进行研究。3D图像通常是模糊的 由于有限的频带，造成了模糊，而且常常是人为的 传统荧光显微镜的空间频率 可以想象。这些问题可以通过光学和/或 计算方法。新一代显微镜的发展 3D成像的速度很快，因此产生了各种各样的 克服焦外模糊和频带限制的方法 传统的显微镜。这些方法包括共焦和 部分共聚焦扫描显微镜、双光子和三光子 光子荧光激发、驻波等。这些 方法改善了成像特性，但不是无模糊的 计算方法可能会进一步提高图像质量。 尽管可以广泛使用连接到 显微镜，计算反卷积的方法并没有享受到 光学仪器的快速而丰富的发展。确实有 不同的商业上可用的反卷积程序包，甚至 这些都是基于最初为3D开发的几种算法 去卷积。这些方法改善了成像性能 但不是没有模糊的，计算方法可能会进一步 提高图像质量。尽管可以广泛获得 连接在显微镜上的计算机，计算反卷积 方法没有享受到快速而丰富的发展 光学仪器。几乎没有商业上可用的 反卷积程序包，甚至那些都是基于前几个 为3D反卷积开发的算法。这些算法是 只有部分成功和显著的改进才能 通过基于彻底的数学运算的算法获得 显微镜和光探测器的型号。此外，a 对现有算法的系统评估尚未完成， 因此，目前还不清楚它们可能实现什么目标。 所提出的研究的长期目标是进一步发展 计算反卷积算法占最多 图像质量下降的重要原因，并提供 算法的使用指南及其功能和 限制。 为了实现这一目标，我们将首先基于 显微镜和光探测器的精确模型，那么我们就做 对这些算法和其他算法进行全面评估，以评估其 并为其使用提供指导方针。

Three-dimensional (3D) fluorescence microscopy is a powerful tool for the study of living specimens. 3D images are normally obscured by out-of-focus blur and often artifactual because of the limited band of spatial frequencies that the conventional fluorescence microscope can image. These problems can be ameliorated by optical and/or computational methods. The development of newer microscopes for 3D imaging has been fast paced resulting on a wide variety of approaches to overcome the out-of focus blur and the band limitation of conventional microscopes. These approaches include confocal and partially confocal scanning microscopes, tow-photon and three- photon fluorescence excitation, standing wave, among other. These approaches improve the imaging properties but are not blur-free and computational approaches may further improve image quality. Despite the widespread availability of computers attached to microscopes, computational deconvolution methods have not enjoyed the fast and rich development of the optical instruments. There are vary few commercially available deconvolution packages and even those are based on the first few algorithms develop for 3D deconvolution. These approaches improve the imaging properties but are not blur-free and computational approaches may further improve image quality. Despite the widespread availability of computers attached to microscopes, computational deconvolution methods have not enjoyed the fast and rich development of the optical instruments. There are very few commercially available deconvolution packages and even those are based on the first few algorithms developed for 3D deconvolution. These algorithms are only partially successful and significant improvements can be obtained with algorithms that are based on a thorough mathematical model for the microscope and the light detector. Furthermore, a systematic evaluation of the exiting algorithms has not been done and thus it is unclear what it is possible to achieve with them. The long-term goal of the research proposed is to further develop computational deconvolution algorithms that account for the most significant sources of degradation in the image and to provide guidelines for the use of the algorithms and for their capabilities and limitations. To achieve this goal we will first derive algorithms based on an accurate model for the microscope and light detector then we will do a thorough evaluation of these and other algorithms to assess their relative merits and to provide guidelines for their use.