Super-resolution structured illumination in optically thick specimens without fluorescent tagging.

This research extends the work of Hoffman et al. to provide both sectioning and super-resolution using random patterns within thick specimens. Two methods of processing structured illumination in reflectance have been developed without the need for a priori knowledge of either the optical system or the modulation patterns. We explore the use of two deconvolution algorithms that assume either Gaussian or sparse priors. This paper will show that while both methods accomplish their intended objective, the sparse priors method provides superior resolution and contrast against all tested targets, providing anywhere from ∼1.6× to ∼2× resolution enhancement. The methods developed here can reasonably be implemented to work without a priori knowledge about the patterns or point spread function. Further, all experiments are run using an incoherent light source, unknown random modulation patterns, and without the use of fluorescent tagging. These additional modifications are challenging, but the generalization of these methods makes them prime candidates for clinical application, providing super-resolved noninvasive sectioning in vivo.

Single-image structured illumination using Hilbert transform demodulation.

Structured illumination microscopy (SIM) achieves sectioning at depth by removing undesired light from out-of-focus planes within a specimen. However, it generally requires at least three modulated images with discrete phase shifts of 0, 120, and 240 deg to produce sectioning. Using a Hilbert transform demodulation, it is possible to produce both sectioning and depth information relative to a reference plane (i.e., a coverslip) using only a single image. The specimen is modulated at a known frequency, and the unmodulated portion of the image is estimated. These two components are used to provide a high-quality sectioned image containing both axial and lateral information of an object. The sectioning resolution with a single image is on par with that of a control three-image SIM. We are also able to show that when used with three images of discrete phase, this method produces better contrast within a turbid media than the traditional SIM technique. Because the traditional SIM requires alignment of three different phases, small differences in optical path length can introduce strong artifacts. Using the single-image technique removes this dependency, greatly improving sectioning in turbid media. Multiple targets with various depths and opaqueness are considered, including human skin in vivo, demonstrating a quick and useful way to provide noninvasive sectioning in real time.

Structured illumination microscopy using random intensity incoherent reflectance.

Depth information is resolved from thick specimens using a modification of structured illumination. By projecting a random projection pattern with varied spatial frequencies that is rotated while capturing images, sectioning can be performed using an incoherent light source in reflectance only. This provides a low-cost solution to obtaining information similar to that produced in confocal microscopy and other methods of structured illumination, without the requirement of complex or elaborate equipment, coherent light sources, or fluorescence. The broad line width of the light emitting diode minimizes artifacts associated with speckle from the laser while also increasing the safety of the instrument. Single diffusers and cascaded diffusers are compared to provide the most efficient method for sectioning at depth. By using reflectance only, in vivo images are produced on a human subject, generating high-contrast images and providing depth information about subsurface objects.