Cinelli A R
Department of Anatomy and Cell Biology, and Video Imaging Facility, State University of New York Health Science Center, Brooklyn 11203, USA.
Methods. 2000 Aug;21(4):349-72. doi: 10.1006/meth.2000.1024.
The distribution of patterns of activity in different brain structures has been related to the encoding and processing of sensory information. Consequently, it is important to be able to image the distribution of these patterns to understand basic brain functions. The spatial resolution of voltage-sensitive dye (VSD) methods has recently been enhanced considerably by the use of video imaging techniques. The main factor that now hampers the resolution of VSD patterns is the inherent limitation of the optical systems. Unfortunately, the intrinsic characteristics of VSD images impose important limitations that restrict the use of general deconvolution techniques. To overcomes this problem, in this study an image restoration procedure has been implemented that takes into consideration the limiting characteristics of VSD signals. This technique is based on applying a set of imaging processing steps. First, the signal-to-noise (S/N) ratio of the images was improved to avoid an increase in the noise levels during the deconvolution procedures. For this purpose, a new filter technique was implemented that yielded better results than other methods currently used in optical imaging. Second, focal plane images were deconvolved using a modification of the well-known nearest-neighbor deconvolution algorithm. But to reduce the light exposure of the preparation and simplify image acquisition procedures, adjacent image planes were modeled according to the in-focus image planes and the empirical point spread function (PSF) profiles. Third, resulting focal plane responses were processed to reduce the contribution of optical responses that originate in distant image planes. This method was found to be satisfactory under simulated and real experimental conditions. By comparing the restored and unprocessed images, it was clearly demonstrated that this method can effectively remove the out-of-focus artifacts and produce focal plane images of better quality. Evaluations of the tissue optical properties allowed assessment of the maximum practical optical section thickness using this deconvolution technique in the optical system tested. Determination of the three-dimensional PSF permitted the correct application of deconvolution algorithms and the removal of the contaminating light arising from adjacent as well as distant optical planes. The implementation of this deconvolution approach in salamander olfactory bulb allowed the detailed study of the laminar distribution of voltage-sensitive changes across the bulb layer. It is concluded that (1) this deconvolution procedure is well suited to deconvolved low-contrast images and offers important advantages over other alternatives; (2) this method can be properly used only when the tissue optical properties are first determined; (3) high levels of light scattering in the tissue reduce the optical section capabilities of this technique as well as other deconvolution procedures; and (4) use of the highest numerical aperture in the objectives is advisable because this improves not only the light-collecting efficiency to detect poor-contrast images, but also the spatial frequency differences between adjacent image planes. Under this condition it is possible to overcome some of the limitations imposed by the light scattering/birefringence of the tissue.
不同脑结构中的活动模式分布与感觉信息的编码和处理相关。因此,能够对这些模式的分布进行成像对于理解基本脑功能很重要。最近,通过使用视频成像技术,电压敏感染料(VSD)方法的空间分辨率有了显著提高。目前阻碍VSD模式分辨率的主要因素是光学系统的固有局限性。不幸的是,VSD图像的固有特性带来了重要限制,限制了一般去卷积技术的使用。为克服这个问题,在本研究中实施了一种图像恢复程序,该程序考虑了VSD信号的限制特性。该技术基于应用一组图像处理步骤。首先,提高图像的信噪比(S/N)以避免在去卷积过程中噪声水平增加。为此,实施了一种新的滤波技术,其效果优于目前光学成像中使用的其他方法。其次,使用对著名的最近邻去卷积算法的改进对焦平面图像进行去卷积。但为了减少标本的光暴露并简化图像采集程序,根据焦内图像平面和经验点扩散函数(PSF)轮廓对相邻图像平面进行建模。第三,对得到的焦平面响应进行处理,以减少源自远处图像平面的光学响应的贡献。在模拟和实际实验条件下,该方法都被证明是令人满意的。通过比较恢复后的图像和未处理的图像,清楚地表明该方法可以有效去除离焦伪像并产生质量更好的焦平面图像。对组织光学特性的评估允许在测试的光学系统中使用这种去卷积技术评估最大实际光学切片厚度。确定三维PSF允许正确应用去卷积算法并去除来自相邻以及远处光学平面的污染光。在蝾螈嗅球中实施这种去卷积方法允许详细研究整个嗅球层电压敏感变化的层状分布。得出的结论是:(1)这种去卷积程序非常适合对低对比度图像进行去卷积,并且比其他方法具有重要优势;(2)只有在首先确定组织光学特性时才能正确使用该方法;(3)组织中的高水平光散射会降低该技术以及其他去卷积程序的光学切片能力;(4)建议使用物镜中最高的数值孔径,因为这不仅提高了检测低对比度图像的光收集效率,还提高了相邻图像平面之间的空间频率差异。在这种情况下,可以克服组织的光散射/双折射带来的一些限制。