Related papers: Fast label-free point-scanning super-resolution im…
Fluorescence microscopy is essential in biological and medical research, providing critical insights into cellular structures. However, limited by optical diffraction and background noise, a substantial amount of hidden information is still…
Feature matching and finding correspondences between endoscopic images is a key step in many clinical applications such as patient follow-up and generation of panoramic image from clinical sequences for fast anomalies localization.…
Volumetric imaging by fluorescence microscopy is often limited by anisotropic spatial resolution from inferior axial resolution compared to the lateral resolution. To address this problem, here we present a deep-learning-enabled…
This paper describes a fast approach to automatic point label de-confliction on interactive maps. The general Map Labeling problem is NP-hard and has been the subject of much study for decades. Computerized maps have introduced interactive…
Endoscopy is the most widely used imaging technique for the diagnosis of cancerous lesions in hollow organs. However, endoscopic images are often affected by illumination artefacts: image parts may be over- or underexposed according to the…
Is self-supervised deep learning (DL) for medical image analysis already a serious alternative to the de facto standard of end-to-end trained supervised DL? We tackle this question for medical image classification, with a particular focus…
Inspired by the capability of structured illumination microscopy in subwavelength imaging, many researchers devoted themselves to investigating this methodology. However, due to the free propagating feature of the traditional structured…
Spectral imaging enables spatially-resolved identification of materials in remote sensing, biomedicine, and astronomy. However, acquisition times require balancing spectral and spatial resolution with signal-to-noise. Hyperspectral imaging…
Phase and polarisation of coherent light are highly perturbed by interaction with microstructural changes in pre-malignant tissue, holding promise for label-free early cancer detection in endoscopically accessible tissues such as the…
Despite the remarkable performance of supervised medical image segmentation models, relying on a large amount of labeled data is impractical in real-world situations. Semi-supervised learning approaches aim to alleviate this challenge using…
Label-Free Multiphoton Microscopy is a very powerful optical microscopy that can be applied to study samples with no need for exogenous fluorescent probes, keeping the main benefits of a Multiphoton approach, like longer penetration depths…
A widely tested approach to overcoming the diffraction limit in microscopy without disturbing the sample relies on substituting widefield sample illumination with a structured light beam. This gives rise to confocal, image-scanning and…
We present a widefield fluorescence microscope that integrates an event-based image sensor (EBIS) with a CMOS image sensor (CIS) for ultra-fast microscopy with spectral distinction capabilities. The EBIS achieves temporal resolution of…
Two-dimensional materials and their van der Waals heterostructures enable a large range of applications, including label-free biosensing. Lattice mismatch and work function difference in the heterostructure material result in strain and…
Light-sheet microscopes must compromise between field of view, optical sectioning, resolution, and detection efficiency. High-numerical-aperture (NA) detection objective lenses provide high resolution but their narrow depth of field fails…
Recently, it was discovered that microsphere can generate super-resolution focusing beyond diffraction limit. This has led to the development of an exciting super-resolution imaging technique -microsphere nanoscopy- that features a record…
Intraoperative optical imaging is essential for surgical precision and patient safety, but current systems present anatomical and fluorescence information separately, causing delays and increasing cognitive load. A unified system for…
With increasingly large data sets, weak lensing measurements are able to measure cosmological parameters with ever greater precision. However this increased accuracy also places greater demands on the statistical tools used to extract the…
In recent years, few-shot segmentation (FSS) models have emerged as a promising approach in medical imaging analysis, offering remarkable adaptability to segment novel classes with limited annotated data. Existing approaches to few-shot…
We present a minimally-invasive endoscope based on a multimode fiber that combines photoacoustic and fluorescence sensing. From the measurement of a transmission matrix during a prior calibration step, a focused spot is produced and…