Abstract
Sensorless adaptive optics is commonly used to compensate specimen-induced aberrations in high-resolution fluorescence microscopy, but requires a bespoke approach to detect aberrations in different microscopy techniques, which hinders its widespread adoption. To overcome this limitation, we propose using wavelet analysis to quantify the loss of resolution due to the aberrations in microscope images. By examining the variations of the wavelet coefficients at different scales, we are able to establish a multi-valued image quality metric that can be successfully deployed in different microscopy techniques. To corroborate our arguments, we provide experimental verification of our method by performing aberration correction experiments in both confocal and STED microscopy using three different specimens.
Highlights
Fluorescence microscopy enables targeted, high-resolution imaging in specimens and its use is fundamental for the advancement of biological sciences [1]
To further assess the quality of the aberration correction reported in Fig. 7, we switched the microscope into 3D stimulated emission depletion (STED) mode, i.e, we enabled both holograms on the spatial light modulator (SLM), one displaying the 2D enhancement phase mask and the other the Z one
In this paper we introduce a novel wavefront sensorless aberration correction algorithm that is based on wavelet analysis
Summary
Fluorescence microscopy enables targeted, high-resolution imaging in specimens and its use is fundamental for the advancement of biological sciences [1]. The scope of this technique is limited in some scenarios, especially when applied to image deep into optically heterogeneous media such as tissue In this case, the presence of aberrations detrimentally affects the contrast and quality of the data that can be recorded [2]. The presence of aberrations detrimentally affects the contrast and quality of the data that can be recorded [2] This situation is further exacerbated when employing super-resolution microscopes [3], where overcoming the diffraction limit is contingent upon accurate shaping of the microscope point-spread functions (PSF), see for example [4,5,6]. Contrary to conventional Fourier analysis, wavelets are able to detect spatially localised variations in the frequency content of images As such they represent an ideal tool to quantify the effect of aberrations on the resolution, regardless of the particular microscopy technique.
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