An LED-Based Structured Illumination Microscope Using A Digital Micromirror Device And GPU Accelerated Image Reconstruction

When combined with computational approaches, fluorescence imaging becomes one of the most powerful tools in biomedical research. It is possible to achieve resolution figures beyond the diffraction limit, and improve the performance and flexibility of high-resolution imaging systems with techniques such as structured illumination microscopy (SIM) reconstruction. In this study, the hardware and software implementation of an LED-based superresolution imaging system using SIM employing GPU accelerated parallel image reconstruction is presented. The sample is illuminated with two-dimensional sinusoidal patterns with various orientations and lateral phase shifts generated using a digital micromirror device (DMD). SIM reconstruction is carried out in frequency space using parallel CUDA kernel functions. Furthermore, a general purpose toolbox for the parallel image reconstruction algorithm and an infrastructure that allows all users to perform parallel operations on images without developing any CUDA kernel code is presented. The developed image reconstruction algorithm was run separately on a CPU and a GPU. Two different SIM reconstruction algorithms have been developed for the CPU as mono-thread CPU algorithm and multi-thread OpenMP CPU algorithm. SIM reconstruction of 1024 × 1024 px images was achieved in 1.49 s using GPU computation, indicating an enhancement by *28 and *20 in computation time when compared with mono-thread CPU computation and multi-thread OpenMP CPU computation, respectively

GPU accelerated real-time multi-functional spectral-domain optical coherence tomography system at 1300 nm.

We present a GPU accelerated multi-functional spectral domain optical coherence tomography system at 1300 nm. The system is capable of real-time processing and display of every intensity image, comprised of 512 pixels by 2048 A-lines acquired at 20 frames per second. The update rate for all four images with size of 512 pixels by 2048 A-lines simultaneously (intensity, phase retardation, flow and en face view) is approximately 10 frames per second. Additionally, we report for the first time the characterization of phase retardation and diattenuation by a sample comprised of a stacked set of polarizing film and wave plate. The calculated optic axis orientation, phase retardation and diattenuation match well with expected values. The speed of each facet of the multi-functional OCT CPU-GPU hybrid acquisition system, intensity, phase retardation, and flow, were separately demonstrated by imaging a horseshoe crab lateral compound eye, a non-uniformly heated chicken muscle, and a microfluidic device. A mouse brain with thin skull preparation was imaged in vivo and demonstrated the capability of the system for live multi-functional OCT visualization

Video-rate multi-color structured illumination microscopy with simultaneous real-time reconstruction

Super-resolved structured illumination microscopy (SR-SIM) is among the fastest fluorescence microscopy techniques capable of surpassing the optical diffraction limit. Current custom-build instruments are able to deliver two-fold resolution enhancement with high acquisition speed. SR-SIM is usually a two-step process, with raw-data acquisition and subsequent, time-consuming post-processing for image reconstruction. In contrast, wide-field and (multi-spot) confocal techniques produce high-resolution images instantly. Such immediacy is also possible with SR-SIM, by tight integration of a video-rate capable SIM with fast reconstruction software. Here we present instant SR-SIM by VIGOR (Video-rate Immediate GPU-accelerated Open-Source Reconstruction). We demonstrate multi-color SR-SIM at video frame-rates, with less than 250 ms delay between measurement and reconstructed image display. This is achieved by modifying and extending high-speed SR-SIM image acquisition with a new, GPU-enhanced, network-enabled image-reconstruction software. We demonstrate high-speed surveying of biological samples in multiple colors and live imaging of moving mitochondria as an example of intracellular dynamics

A survey of real-time crowd rendering

In this survey we review, classify and compare existing approaches for real-time crowd rendering. We first overview character animation techniques, as they are highly tied to crowd rendering performance, and then we analyze the state of the art in crowd rendering. We discuss different representations for level-of-detail (LoD) rendering of animated characters, including polygon-based, point-based, and image-based techniques, and review different criteria for runtime LoD selection. Besides LoD approaches, we review classic acceleration schemes, such as frustum culling and occlusion culling, and describe how they can be adapted to handle crowds of animated characters. We also discuss specific acceleration techniques for crowd rendering, such as primitive pseudo-instancing, palette skinning, and dynamic key-pose caching, which benefit from current graphics hardware. We also address other factors affecting performance and realism of crowds such as lighting, shadowing, clothing and variability. Finally we provide an exhaustive comparison of the most relevant approaches in the field.Peer ReviewedPostprint (author's final draft