25 papers · ranked by Valyu relevance
Bo Wang, Yahui Long, Yuting Bai, Jiawei Luo + 1 more
In this paper, we propose STCGAN, a cellular deconvolution method based on a cycle-consistent generative adversarial network. We first employ a cycle-consistent adversarial network to capture the complex spatial gene expression patterns, ensuring that the model can accurately depict the spatial structure. Next, we…
Xiangyu Qian, Jing Liu, Yunqing Tang, Luru Dai + 1 more
Fluorescence microscopy images are degraded by noise and diffraction-induced blur, which compromise structural fidelity and limit quantitative analysis. Supervised deep learning methods achieve impressive restoration performance but require large-scale paired datasets that are difficult to obtain in practice. To…
Hayato Ikoma, Michael Broxton, Takamasa Kudo, Gordon Wetzstein
Deconvolution is widely used to improve the contrast and clarity of a 3D focal stack collected using a fluorescence microscope. But despite being extensively studied, deconvolution algorithms can introduce reconstruction artifacts when their underlying noise models or priors are violated, such as when imaging…
Brendan F. Miller, Lyla Atta, Arpan Sahoo, Feiyang Huang + 1 more
Recent technological advancements have enabled spatially resolved transcriptomic profiling but at multi-cellular pixel resolution, thereby hindering the identification of cell-type spatial co-localization patterns. We developed STdeconvolve as an unsupervised approach to deconvolve underlying cell-types comprising such…
Martijn R. Molenaar, Mohammed Shahraz, Jeany Delafiori, Andreas Eisenbarth + 3 more
'Andreas Eisenbarth' 'Måns Ekelöf' 'Luca Rappez' 'Theodore Alexandrov'] Imaging mass spectrometry (MS) is becoming increasingly applied for single-cell analyses. Multiple methods for imaging MS-based single-cell metabolomics were proposed, including our recent method SpaceM. An important step in imaging MS-based…
Lena-Marie Woelk, Sukanya A. Kannabiran, Valerie Brock, Christine E. Gee + 4 more
Live cell Ca^2+^ fluorescence microscopy is a cornerstone of cellular signaling analysis and imaging. The demand for high spatial and temporal imaging resolution is, however, intrinsically linked to a low signal-to-noise ratio (SNR) of the acquired spatio-temporal image data, which impedes subsequent image analysis.…
Yiwei Hou, Wenyi Wang, Yunzhe Fu, Xichuan Ge + 2 more
Despite the grand advances in fluorescence microscopy, the photon budget of fluorescent molecules remains the fundamental limiting factor for major imaging parameters, such as temporal resolution, duration, contrast, and even spatial resolution. Computational methods can strategically utilize the fluorescence photons…
Bastien Chassagnol, Grégory Nuel, Étienne Becht
Although bulk transcriptomic analyses have significantly contributed to an enhanced comprehension of multifaceted diseases, their exploration capacity is impeded by the heterogeneous compositions of biological samples. Indeed, by averaging expression of multiple cell types, RNA-Seq analysis is oblivious to variations…
Alexander Wong, Xiao Yu Wang, Maud Gorbet
Fluorescence microscopy is widely used for the study of biological specimens. Deconvolution can significantly improve the resolution and contrast of images produced using fluorescence microscopy; in particular, Bayesian-based methods have become very popular in deconvolution fluorescence microscopy. An ongoing…
Peter Haub, Tobias Meckel
Colour deconvolution is a method used in diagnostic brightfield microscopy to transform colour images of multiple stained biological samples into images representing the stain concentrations. It is applied by decomposing the absorbance values of stain mixtures into absorbance values of single stains. The method assumes…
Alexander Wong, Xiaoyu Wang, Maud Gorbet
Fluorescence microscopy is widely used for the study of biological specimens. Deconvolution can significantly improve the resolution and contrast of images produced using fluorescence microscopy; in particular, Bayesian-based methods have become very popular in deconvolution fluorescence microscopy. An ongoing…
Authors not listed
4D live fluorescence microscopy is often compromised by prolonged high intensity illumination which induces photobleaching and phototoxic effects that generate photo-induced artifacts and severely impair image continuity and detail recovery. To address this challenge, we propose the CellINR framework, a case-specific…
M Laasmaa, M Vendelin, P Peterson
Although confocal microscopes have considerably smaller contribution of out-of-focus light than widefield microscopes, the confocal images can still be enhanced mathematically if the optical and data acquisition effects are accounted for. For that, several deconvolution algorithms have been proposed. As a practical…
Haohong Gan, Shiyi Peng, Hailian Hu, Xuan You + 4 more
The resolving power of optical microscopy is fundamentally constrained by the diffraction of light, limiting our ability to visualize subcellular structures. Computational methods, particularly deconvolution, can restore blurred images but critically depend on an accurate point spread function (PSF), whose estimation…
Imen Boujmil, Giancarlo Ruocco, Marco Leonetti
Super resolution techniques are an excellent alternative to wide field microscopy, providing high resolution also in (typically fragile) biological sample. Among the various super resolution techniques, Structured Illumination Microscopy (SIM) improve resolution by employing multiple illumination patterns to be…
Alba Lomas Redondo, Jose M. Sánchez Velázquez, Álvaro J. García Tejedor, Víctor Javier Sánchez–Arévalo
Within this systematic review we examine the role of Artificial Intelligence (AI) and Deep Learning (DL) in the development of cellular deconvolution tools, with an special focus on their application to the analysis of transcriptomics data from RNA sequencing. We emphasize the critical importance of high–quality…
Mark C. Leake
Recent technological advances in cutting-edge ultrasensitive fluorescence microscopy have allowed single-molecule imaging experiments in living cells across all three domains of life to become commonplace. Single-molecule live-cell data is typically obtained in a low signal-to-noise ratio (SNR) regime sometimes only…
Benjamin Kesler, Guoliang Li, Alexander Thiemicke, Rohit Venkat + 1 more
'Gregor Neuert'] To characterize cell types, cellular functions and intracellular processes, an understanding of the differences between individual cells is required. Although microscopy approaches have made tremendous progress in imaging cells in different contexts, the analysis of these imaging data sets is a…
Tess Homan, Sylvain Monnier, Cécile Jebane, Hélène Delanoë‐Ayari
We present an in-depth investigation of a fully automated Fourier-based analysis to determine the cell size and the width of its distribution in 3D biological tissues. The results are thoroughly tested using generated images, and we offer valuable criteria for image acquisition settings to optimize accuracy. We…
Authors not listed
Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI-MSI) is a powerful technique for molecular analysis of surfaces; however, its application of single cell studies has not been previously published. In the current work, a commercial DESI setup (DESI XS) coupled to a mass spectrometer was used to analyze…
Adeleke Maradesa, Baptiste Py, Ting Hei Wan, Mohammed B. Effat + 1 more
Electrochemical impedance spectroscopy (EIS) is a characterization technique used widely in electrochemistry. Obtaining EIS data is simple when modern electrochemical workstations are used; however, analyzing EIS spectra is still a considerable quandary. The distribution of relaxation times (DRT) has emerged as a…
Authors not listed
Scanning ion conductance microscopy (SICM) offers non-contact, label-free imaging of live cells with nanometer-scale resolution. However, its conventional imaging mode is inherently slow due to repeated vertical scanning, limiting temporal resolution and causing inertial issues. Here, we present Scanning Counter Ion…
Denice van Herwerden, Jake O'Brien, Sascha Lege, Bob Pirok + 2 more
Fragment deconvolution is a crucial step during componentization of non-targeted analysis (NTA) high-resolution mass spectrometry (HRMS) data, aiming to filter out false positive (FP) signals that do not belong to the component. Moreover, inclusion of FP fragments could lead to, for example, wrong identification…
Authors not listed
Self-organizing tissues, such as organoids, offer transformative potential beyond healthcare by enabling the sustainable production of advanced materials. Resource scarcity and global warming drive the need for innovative fabrication solutions. This prospective review explores developmental biology as a manufacturing…
Juerg Straubhaar, Alexandria D’Souza, Zachary Niziolek, Bogdan Budnik
Single-cell analysis has clearly established itself in biology and biomedical fields as an invaluable tool that allows one to comprehensively understand the relationship between cells, including their types, states, transitions, trajectories, and spatial position. Scientific methods such as fluorescence labeling…