Stochastically structured illumination microscopy scan less super resolution imaging.

In super-resolution, a varying illumination image stack is required. This enriched dataset typically necessitates precise mechanical control and micron-scale optical alignment and repeatability. Here, we introduce a novel methodology for super-resolution microscopy called stochastically structured illumination microscopy (SIM), which bypasses the need for illumination control exploiting instead the random, uncontrolled movement of the target object. We tested our methodology within the clinically relevant ophthalmoscopic setting, harnessing the inherent saccadic motion of the eye to induce stochastic displacement of the illumination pattern on the retina. We opted to avoid human subjects by utilizing a phantom eye model featuring a retina composed of human induced pluripotent stem cells (iPSC) retinal neurons and replicating the ocular saccadic movements by custom actuators. Our findings demonstrate that SIM unlocks scan-less super-resolution with a resolution enhancement of 1.91, with promising prospects also beyond ophthalmoscopy applications such as active matter or atmospheric/astronomical observation.