PARAMETRIC BLIND DECONVOLUTION OF MICROSCOPIC IMAGES

共焦扫描显微镜（CSM）现在广泛用于三个- 固定标本的三维（3D）可视化。然而，生活 样品经常被高强度激光损坏和/或漂白 CSM所需的激发光。一个常见的解决方案是打开 共焦光圈轻微，从而允许更多的光到达 检测器然而，更大的共焦孔径也接受更多的非共焦。 聚焦光线并降低CSM的深度分辨率。 丢失的 可以使用计算反卷积算法来恢复分辨率。 即使是严格的共焦显微镜也受益于增加的 解卷积算法提供的分辨率。大多数调制解调器CSM 配有一台主机，可以将共焦图像的3D堆栈数字化。 尽管计算机的可用性，共焦图像的解卷积 还没有被广泛使用。其中一个关键原因是， 反卷积算法需要点扩展的准确知识， 描述显微镜的函数（PSF）。 在现代CSM中， PSF的测量或计算充其量是困难的。在这些 在某些情况下，需要估计PSF和样品荧光 分布同时从图像，一种方法称为盲 解卷积（BD）。BD的当前方法是缓慢的，因为它们 逐点估计PSF。 这项研究的长期目标是提供更快、更多的 鲁棒的计算反卷积算法， 测量或计算显微镜的PSF。 为了实现这一目标，使用PSF的物理物理模型 这取决于少量的未知参数，然后估计 将派生方法来同时获得这些参数的值 与标本荧光分布。虽然长期目标 是BD的部分共焦图像，非共焦显微镜用户将 他们也从这项研究的结果中受益。

Confocal scanning microscopes (CSM) are now widely used for three- dimensional (3D) visualization of fixed specimens. However, living specimens are often damaged and/or bleached by the high intensity laser excitation light required by the CSM. A common solution is to open the confocal aperture slightly and thus allow more light to reach the detector. A larger confocal aperture, however, accepts also more out-of- focus light and degrades the depth resolution of the CSM. The lost resolution can be recovered using computational deconvolution algorithms. Even the strictly confocal microscope benefits from the increased resolution that deconvolution algorithms provide. Most of the modem CSM's come with a host computer that digitizes 3D stacks of confocal images. Despite the availability of a computer, deconvolution of confocal images has not been widely used. One of the key reasons is that most deconvolution algorithms require accurate knowledge of the point-spread- function (PSF) that describes the microscope. In modern CSM's, the measurement or computation of the PSF is difficult at best. In these cases, it is necessary to estimate the PSF and the specimen fluorescence distribution simultaneously from the image, an approach called blind deconvolution (BD). Current methods for the BD are slow because they estimate the PSF point by point. The long term goal of the research proposed is to provide faster and more robust computational deconvolution algorithms that do not require measuring or computing the microscope's PSF. To achieve this goal, a mathematical-physical model for the PSF is used that depends on a small number of unknown parameters, then estimation methods will be derived to obtain the values of these parameters together with the specimen fluorescent distribution. Although the long term goal is BD of partially confocal images, nonconfocal microscope users will also benefit from the results of this research.