mmSIM: an open toolbox for accessible structured illumination microscopy

Abstract

Since the first practical super-resolution structured illumination fluorescence microscopes (SIM) were demonstrated more than two decades ago, the method has become increasingly popular for a wide range of bioimaging applications. The high cost and relative inflexibility of commercial systems, coupled with the conceptual simplicity of the approach and the desire to exploit and customize existing hardware, have led to the development of a large number of home-built systems. Several detailed hardware designs are available in the scientific literature, complemented by open-source software tools for SIM image validation and reconstruction. However, there remains a lack of simple open-source software to control these systems and manage the synchronization between hardware components, which is critical for effective SIM imaging. This article describes a new suite of software tools based on the popular Micro-Manager package, which enable the keen microscopist to develop and run a SIM system. We use the software to control two custom-built, high-speed, spatial light modulator-based SIM systems, evaluating their performance by imaging a range of fluorescent samples. By simplifying the process of SIM hardware development, we aim to support wider adoption of the technique. This article is part of the Theo Murphy meeting issue ‘Super-resolution structured illumination microscopy (part 1)’.

Super-resolution structured illumination microscopy: past, present and future

“…In parallel, the rapidly evolving field of computational microscopy is paving the way to circumvent the resolution limit without the necessity of specialized hardware reducing the complexity of instrumentation. For example, machine learning (ML) assisted denoising has been demonstrated to improve SIM reconstructions by reducing artifacts and boosting the effective resolution for 2D-SIM [65,66,70,71,[81][82][83][84]. Thus, by combining physical data acquisition with smart image processing algorithms, previously inaccessible information can be recovered.…”

Automatic Multi-functional Integration Program (AMFIP) towards all-optical mechano-electrophysiology interrogation

“…These microcontrollers generate analog and digital signals to modulate optoelectronic devices. For example, the NI data acquisition card (DAQ; National Instrument Corp.) is utilized to control the frame acquisition of the camera and switch of the laser channels [ 10 ]. An Arduino-based system is applied to modulate selective-plane illumination microscopy (SPIM) [ 11 ].…”