Publications related to Spatially-Variant CNN-Based Point Spread Function Estimation for Blind Deconvolution and Depth Estimation in Optical Microscopy

Related publications (37)

Experimental comparison of X-ray ptychographic and holographic nanotomography of metal-stained neuronal tissue

Hard X-ray nanotomography is a promising technology for nondestructive imaging of biological tissues with three-dimensional isotropic resolution. The implementation of fourth-generation synchrotron sources brings coherent X-ray microscopy to the central st ...

Optica Publishing Group2025

How data structures affect generalization in Kernel Methods and Deep Learning

Umberto Maria Tomasini

Artificial Intelligence has revolutionized numerous fields, driving advancements in healthcare, finance, and autonomous systems. At the core of this revolution lies Deep Learning---algorithms that learn representations from data through computational layer ...

EPFL2025

A Bayesian Interpretation of Adaptive Low-Rank Adaptation

Haolin Chen

Motivated by the sensitivity-based importance score of the adaptive low-rank adaptation (AdaLoRA), we utilize more theoretically supported metrics, including the signal-to-noise ratio (SNR), along with the Improved Variational Online Newton (IVON) optimize ...

Institute of Electrical and Electronics Engineers Inc.2025

Optical Metasurfaces for the Next-Generation Biosensing and Bioimaging

Hatice Altug

Recent advances in this understanding of light-matter interactions, combined with innovations in the design and fabrication of large-scale nanostructured metasurfaces, have enabled transformative approaches to biosensing and bioimaging. This review delves ...

2025

Live-cell imaging powered by computation

Suliana Manley

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preservi ...

Nature Portfolio2024

Compact and effective photon-resolved image scanning microscope

Giorgio Tortarolo

Fluorescence confocal laser-scanning microscopy (LSM) is one of the most popular tools for life science research. This popularity is expected to grow thanks to single-photon array detectors tailored for LSM. These detectors offer unique single-photon spati ...

Spie-Soc Photo-Optical Instrumentation Engineers2024

Fluorescence microscopy: A statistics-optics perspective

Aleksandra Radenovic

Fundamental properties of light unavoidably impose features on images collected using fluorescence microscopes. Accounting for these features is often critical in quantitatively interpreting microscopy images, especially those gathering information at scal ...

Amer Physical Soc2024

A continuous-wave and pulsed X-band electron spin resonance spectrometer operating in ultra-high vacuum for the study of low dimensional spin ensembles

Giovanni Boero, Fabio Donati, Soyoung Oh

We report the development of a continuous-wave and pulsed X-band electron spin resonance (ESR) spectrometer for the study of spins on ordered surfaces down to cryogenic temperatures. The spectrometer operates in ultra-high vacuum and utilizes a half-wavele ...

Aip Publishing2024

Subsurface fluorescence time-of-flight imaging using a large-format single-photon avalanche diode sensor for tumor depth assessment

Edoardo Charbon, Claudio Bruschini, Arin Can Ülkü

Significance: Fluorescence guidance is used clinically by surgeons to visualize anatomical and/or physiological phenomena in the surgical field that are difficult or impossible to detect by the naked eye. Such phenomena include tissue perfusion or molecula ...

SPIE Society of Photo-optical Instrumentation Engineers2024

Advances in High-Speed, Multiparametric Atomic Force Microscopy

Santiago Harald Andany

After decades of technological advancements, high-speed atomic force microscopy (HS-AFM) has emerged as a powerful technique for visualizing dynamic processes. At the nanoscale, the AFM provides valuable insights into the sample by sensing minute interacti ...

EPFL2024

The multimodality cell segmentation challenge: toward universal solutions

Maxime Emmanuel Scheder, Jun Ma, Sahand Jamal Rahi, Xin Yang, Vojislav Gligorovski, Marco Labagnara

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimen ...

Nature Publishing Group2024

Electron-beam based nanoscale quantum controls

Hoda Shirzad

Advancing quantum technologies depends on the precise control of individual quantum systems, the so-called qubits, and the exploitation of their quantum properties. Nowadays, expanding the number of qubits to be entangled is at the core of the developments ...

EPFL2024

Controlling crystal cleavage in focused ion beam shaped specimens for surface spectroscopy

Philip Johannes Walter Moll, Matthias Carsten Putzke

Our understanding of quantum materials is commonly based on precise determinations of their electronic spectrum by spectroscopic means, most notably angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy. Both require atomicall ...

Aip Publishing2024

Label-Free Techniques for Probing Biomolecular Condensates

Akhil Sai Naidu, Aleksandra Radenovic, Wayne Yang Wen Wei, Helena Miljkovic, Khalid Ashraf Mohie Ibrahim

Biomolecular condensates play important roles in a wide array of fundamental biological processes, such as cellular compartmentalization, cellular regulation, and other biochemical reactions. Since their discovery and first observations, an extensive and e ...

Amer Chemical Soc2024

Surface passivation and functionalisation for mass photometry

Laila Abdelaziz Abdelmoniem Elfeky, Suliana Manley, Jenny Sülzle

Interferometric scattering (iSCAT) microscopy enables the label-free observation of biomolecules. Consequently, single-particle imaging and tracking with the iSCAT-based method known as mass photometry (MP) is a growing area of study. However, establishing ...

Wiley2024

Aggregating Spatial and Photometric Context for Photometric Stereo

David Honzátko

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

EPFL2024

Ghost imaging using two SPAD array detectors: a parameter study towards the realization of a 3D quantum microscope

Edoardo Charbon, Claudio Bruschini, Paul Mos, Yang Lin

Quantum ghost imaging can be an important tool in making optical measurements. One of the most useful aspects of ghost imaging is the unique ability to correlate two sets of independently collected information. We aim to use the principles of ghost imaging ...

Spie-Int Soc Optical Engineering2024

Random matrix methods for high-dimensional machine learning models

Antoine Philippe Michel Bodin

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

Polydopamine-coated photoautotrophic bacteria for improving extracellular electron transfer in living photovoltaics

Ardemis Anoush Boghossian, Melania Reggente, Hanxuan Wang, Charlotte Elisabeth Marie Roullier, Mohammed Mouhib

Living photovoltaics are microbial electrochemical devices that use whole cell–electrode interactions to convert solar energy to electricity. The bottleneck in these technologies is the limited electron transfer between the microbe and the electrode surfac ...

2024

Partial discharge localization in power transformer tanks using machine learning methods

Farhad Rachidi-Haeri, Marcos Rubinstein, Hamidreza Karami

This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...

Nature Publishing Group2024