Huafeng Ding

Bio: Huafeng Ding is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Light scattering & Scattering. The author has an hindex of 17, co-authored 24 publications receiving 1849 citations.

Spatial light interference microscopy (SLIM)

Abstract: We present spatial light interference microscopy (SLIM) as a new optical microscopy technique, capable of measuring nanoscale structures and dynamics in live cells via interferometry. SLIM combines two classic ideas in light imaging: Zernike’s phase contrast microscopy, which renders high contrast intensity images of transparent specimens, and Gabor’s holography, where the phase information from the object is recorded. Thus, SLIM reveals the intrinsic contrast of cell structures and, in addition, renders quantitative optical path-length maps across the sample. The resulting topographic accuracy is comparable to that of atomic force microscopy, while the acquisition speed is 1,000 times higher. We illustrate the novel insight into cell dynamics via SLIM by experiments on primary cell cultures from the rat brain. SLIM is implemented as an add-on module to an existing phase contrast microscope, which may prove instrumental in impacting the light microscopy field at a large scale.

Spatial light interference microscopy (SLIM)

Abstract: We present SLIM, a new optical method measuring optical pathlength changes of 0.3 nm spatially and 0.03nm temporally. SLIM combines two classic ideas in light imaging: Zernike’s phase contrast microscopyand Gabor’s holography.

Fourier transform light scattering of inhomogeneous and dynamic structures.

Abstract: Fourier transform light scattering (FTLS) is a novel experimental approach that combines optical microscopy, holography, and light scattering for studying inhomogeneous and dynamic media. In FTLS the optical phase and amplitude of a coherent image field are quantified and propagated numerically to the scattering plane. Because it detects all the scattered angles (spatial frequencies) simultaneously in each point of the image, FTLS can be regarded as the spatial equivalent of Fourier transform infrared spectroscopy, where all the temporal frequencies are detected at each moment in time.

Spatial light interference microscopy and fourier transform light scattering for cell and tissue characterization

Abstract: Methods and apparatus for rendering quantitative phase maps across and through transparent samples. A broadband source is employed in conjunction with an objective, Fourier optics, and a programmable two-dimensional phase modulator to obtain amplitude and phase information in an image plane. Methods, referred to as Fourier transform light scattering (FTLS), measure the angular scattering spectrum of the sample. FTLS combines optical microscopy and light scattering for studying inhomogeneous and dynamic media. FTLS relies on quantifying the optical phase and amplitude associated with a coherent image field and propagating it numerically to the scattering plane. Full angular information, limited only by the microscope objective, is obtained from extremely weak scatterers, such as a single micron-sized particle. A flow cytometer may employ FTLS sorting.

Instantaneous Spatial Light Interference Microscopy.

Abstract: We present Instantaneous Spatial Light Interference Microscopy (iSLIM) as a new quantitative phase method that combines the benefits of white light illumination in Zernike’s phase contrast microscopy and phase stability associated diffraction phase microscopy. iSLIM is implemented as an add-on module to a commercial phase contrast microscope, and enables new features to quantitative phase imaging: diminished speckle effects due to white light illumination, multimodal investigation potential due to overlaying with other modalities of the microscope (e.g. fluorescence, DIC, phase contrast), and spectroscopic potential due to the broad band light. We show proof of principle results by multicolor phase imaging of microsphere and red blood cells, and dynamic imaging of nanoscale cell membrane fluctuations.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Quantitative phase imaging in biomedicine

Abstract: Quantitative phase imaging (QPI) has emerged as a valuable method for investigating cells and tissues. QPI operates on unlabelled specimens and, as such, is complementary to established fluorescence microscopy, exhibiting lower phototoxicity and no photobleaching. As the images represent quantitative maps of optical path length delays introduced by the specimen, QPI provides an objective measure of morphology and dynamics, free of variability due to contrast agents. Owing to the tremendous progress witnessed especially in the past 10–15 years, a number of technologies have become sufficiently reliable and translated to biomedical laboratories. Commercialization efforts are under way and, as a result, the QPI field is now transitioning from a technology-development-driven to an application-focused field. In this Review, we aim to provide a critical and objective overview of this dynamic research field by presenting the scientific context, main principles of operation and current biomedical applications. Over the past 10–15 years, quantitative phase imaging has moved from a research-driven to an application-focused field. This Review presents the main principles of operation and representative basic and clinical science applications.

Phase recovery and holographic image reconstruction using deep learning in neural networks

Abstract: Phase recovery from intensity-only measurements forms the heart of coherent imaging techniques and holography. In this study, we demonstrate that a neural network can learn to perform phase recovery and holographic image reconstruction after appropriate training. This deep learning-based approach provides an entirely new framework to conduct holographic imaging by rapidly eliminating twin-image and self-interference-related spatial artifacts. This neural network-based method is fast to compute and reconstructs phase and amplitude images of the objects using only one hologram, requiring fewer measurements in addition to being computationally faster. We validated this method by reconstructing the phase and amplitude images of various samples, including blood and Pap smears and tissue sections. These results highlight that challenging problems in imaging science can be overcome through machine learning, providing new avenues to design powerful computational imaging systems.

Spatial light interference microscopy (SLIM)

Abstract: We present spatial light interference microscopy (SLIM) as a new optical microscopy technique, capable of measuring nanoscale structures and dynamics in live cells via interferometry. SLIM combines two classic ideas in light imaging: Zernike’s phase contrast microscopy, which renders high contrast intensity images of transparent specimens, and Gabor’s holography, where the phase information from the object is recorded. Thus, SLIM reveals the intrinsic contrast of cell structures and, in addition, renders quantitative optical path-length maps across the sample. The resulting topographic accuracy is comparable to that of atomic force microscopy, while the acquisition speed is 1,000 times higher. We illustrate the novel insight into cell dynamics via SLIM by experiments on primary cell cultures from the rat brain. SLIM is implemented as an add-on module to an existing phase contrast microscope, which may prove instrumental in impacting the light microscopy field at a large scale.