Related papers: A fibered interference scanning optical microscope…
Advancement in mid-infrared (MIR) technology has led to promising biomedical applications of MIR spectroscopy, such as liquid biopsy or breath diagnosis. On the contrary, MIR microscopy has been rarely used for live biological samples in an…
Bright-field microscopy, a cost-effective solution for live-cell culture, is often the only resource available, along with standard CPUs, for many low-budget labs. The inherent challenges of bright-field images -- their noisiness, low…
Automated cell segmentation in microscopy images is essential for biomedical research, yet conventional methods are labor-intensive and prone to error. While deep learning-based approaches have proven effective, they often require large…
Elasticity is a fundamental cellular property that is related to the anatomy, functionality and pathological state of cells and tissues. However, current techniques based on cell deformation, atomic force microscopy or Brillouin scattering…
Accurate segmentation of live cell images has broad applications in clinical and research contexts. Deep learning methods have been able to perform cell segmentations with high accuracy; however developing machine learning models to do this…
Counting cells in fluorescent microscopy is a tedious, time-consuming task that researchers have to accomplish to assess the effects of different experimental conditions on biological structures of interest. Although such objects are…
This work demonstrates a multi-lens microscopic imaging system that overlaps multiple independent fields of view on a single sensor for high-efficiency automated specimen analysis. Automatic detection, classification and counting of various…
Fluorescence microscopes can record the dynamics of living cells with high spatio-temporal resolution in a single plane. However, monitoring rapid and dim fluorescence fluctuations, e.g induced by neuronal activity in the brain, remains…
Capturing biological specimens at large scales with sub-micron resolution is crucial for biomedical research, but conventional cameras often can't handle the pixel requirements. While most microscopes use motorized stages to move samples…
Data-driven cell tracking and segmentation methods in biomedical imaging require diverse and information-rich training data. In cases where the number of training samples is limited, synthetic computer-generated data sets can be used to…
Imaging through optical multimode fibers (MMFs) has the potential to enable hair-thin endoscopes that reduce the invasiveness of imaging deep inside tissues and organs. Current approaches predominantly require active wavefront shaping and…
Single-molecule detection enables direct observation of individual biomolecular events, providing mechanistic insights into biological processes and offering a powerful tool for disease diagnostics. However, the fundamental scale mismatch…
Lightsheet microscopy is a powerful 3-D imaging technique that addresses limitations of traditional optical and confocal microscopy but suffers from a low penetration depth and reduced image quality at greater depths. Multiview lightsheet…
Super-resolution fluorescence microscopy provides unprecedented insight into cellular and subcellular structures. However, going "beyond the diffraction barrier" comes at a price since most far-field super-resolution imaging techniques…
Replacing electrons with photons is a compelling route towards light-speed, highly parallel, and low-power artificial intelligence computing. Recently, all-optical diffractive neural deep neural networks have been demonstrated. However, the…
Computational hardware designed to mimic biological neural networks holds the promise to resolve the drastically growing global energy demand of artificial intelligence. A wide variety of hardware concepts have been proposed, and among…
Optical frequency combs have revolutionised time and frequency metrology [1, 2]. The advent of microresonator-based frequency combs ('microcombs' [3-5]) is set to lead to the miniaturisation of devices that are ideally suited to a wide…
Background Analyzing images to accurately estimate the number of different cell types in the brain using automatic methods is a major objective in neuroscience. The automatic and selective detection and segmentation of neurons would be an…
The membrane curvature of cells and intracellular compartments continuously adapts to enable cells to perform vital functions, from cell division to signal trafficking. Understanding how membrane geometry affects these processes in vivo is…
Nanophotonic devices excel at confining light into intense hot spots of the electromagnetic near fields, creating unprecedented opportunities for light-matter coupling and surface-enhanced sensing. Recently, all-dielectric metasurfaces with…