Every experimenter using a fluorescence microscope wants to have as detailed information of his structure of interest as possible. The problem here lies in the limited capability of an optical system to produce a realistic picture. Every light source, for example a GFP-coupled protein, emits scattered light. In practice this can lead to a blurry signal, depending on the thickness of the specimen. To overcome this problem, different approaches have been developed in the past. On the one hand, confocal microscopy excludes out-of-focus information by using a sophisticated positioning of pinholes in the excitation and emission light pathway. This leads to an image with high z-resolution (= low focal depth) and without any out-of-focus contribution. Due to the small confocal volume which creates the image during the scanning point after point, the user has to work with a high light dose provided by a laser. So the benefit of a sharper image is offset by a considerable disadvantage. The high energy amount may produce bleaching and in general damage to the cell (phototoxicity). Therefore, a confocal system may not always be the best choice for life cell imaging. A conventional (widefield) fluorescence system has advantages in terms of higher sensitivity with lower exposure. With a low light dose cells are not damaged and fluorescence stays longer. As already mentioned, this benefit is gained at the expense of worse resolution.
To solve this problem it makes sense to look at a very small structure – a sub-resolution latex bead. Watching this 3D fluorescent object with a fluorescence microscope in xy orientation leads to the projection of a glowing point with a blurry surrounding (s. Figure 1). An acquisition of a z-stack results in the following depiction: The side view of the bead resembles two cones standing on top of each other's apex. This is due to stray light which is recorded during the z-stack acquisition. The goal of deconvolution is to subtract this "false" information from the real situation with the help of a mathematical calculation.
To understand the basics of this procedure it is necessary to introduce a special term which is very often utilized when it comes to deconvolution: Point spread function.
To repeat, if an experimenter wants to obtain a three-dimensional impression of his object, he is forced to assemble a 3D image out of a sequence of 2D images. That is why one has to record a z-stack and put these pictures together. The result of such an approach is shown in Figure 1 (right). As one can see, the product is not a perfectly round sphere (latex bead) which is due to the problem with stray light described in the first paragraph. In principle, this phenomenon stems from the limited skills of an optical system to describe a point-shaped light source. The signal which passes through the lenses of the microscope is distorted depending on the adjustment of the system, the wavelength, the objective and its numerical aperture (NA) or the refraction index of the immersion media and other parameters. The result of all these influences – concerning the depiction of a point-shaped object by an optical system – is described as a point spread function (PSF). In physical terms, the object is convoluted (folded) by the PSF. This also means that by knowing the PSF it is possible to unfold the object again, which is logically named deconvolution (s. Figure 2).
Fig. 2: Point spread function (PSF). Depiction of a point-shaped object by an optical system is influenced by several parameters like the adjustment of the system, the objective and its numerical aperture and the refraction index of the immersion media. Altogether this leads to a distortion of the object, which can be described by a mathematical value, the PSF. In physical language the object is convoluted (folded) by the PSF. Logically, by knowing the PSF, the object can be unfolded. This process is called deconvolution.
The question in this respect is how to get the PSF. In principle there are two ways to gain this information. An admittedly more precise method is the measurement of the PSF. For this technique one has to determine the PSF of a sub-resolution object with a known dimension. This route is not very often taken for practical reasons. An easier and faster way is the calculation of the PSF. Providing information like excitation and emission wavelength peaks or the NA of the used objective, this theoretical value is estimated by a computer algorithm.
As mentioned above, with knowledge of the PSF – even if it is a theoretical figure – it is possible to reverse the convolution which was made by the optical system. But before deconvolution can be started, several criteria have to be fulfilled to get reliable and high quality results. Of course, the better the original pictures are, the better the deconvolved image will be.
A very important requirement for deconvolution is a high quality